Alan E. Gelfand

Journal Article Test · March 1, 2024 Quantile regression continues to increase in usage, providing a useful alternative to customary mean regression. Primary implementation takes the form of so-called multiple quantile regression, creating a separate regression for each quantile of interest. ... Full text Cite

Generative spatial generalized dissimilarity mixed modelling (spGDMM): An enhanced approach to modelling beta diversity

Journal Article Methods in Ecology and Evolution · January 1, 2024 Turnover, or change in the composition of species over space and time, is one of the primary ways to define beta diversity. Inferring what factors impact beta diversity is not only important for understanding biodiversity processes but also for conservatio ... Full text Cite

Assessing space and time changes in daily maximum temperature in the Ebro basin (Spain) using model-based statistical tools

Journal Article International Journal of Climatology · December 30, 2023 There is continuing interest in the investigation of change in temperature over space and time. For this analysis, we offer statistical tools to illuminate changes temporally, at desired temporal resolution, and spatially, using data generated from suitabl ... Full text Cite

Space-time multi-level modeling for zooplankton abundance employing double data fusion and calibration

Journal Article Environmental and Ecological Statistics · December 1, 2023 An important objective for marine biologists is to forecast the distribution and abundance of planktivorous marine predators. To do so, it is critically important to understand the spatiotemporal dynamics of their prey. Here, the prey we study are zooplank ... Full text Cite

Mechanistic modeling of climate effects on redistribution and population growth in a community of fish species.

Journal Article Global change biology · November 2023 Understanding community responses to climate is critical for anticipating the future impacts of global change. However, despite increased research efforts in this field, models that explicitly include important biological mechanisms are lacking. Quantifyin ... Full text Cite

Joint multivariate and functional modeling for plant traits and reflectances

Journal Article Environmental and Ecological Statistics · September 1, 2023 The investigation of leaf-level traits in response to varying environmental conditions has immense importance for understanding plant ecology. Remote sensing technology enables measurement of the reflectance of plants to make inferences about underlying tr ... Full text Cite

SPATIAL QUANTILE AUTOREGRESSION FOR SEASON WITHIN YEAR DAILY MAXIMUM TEMPERATURE DATA

Journal Article Annals of Applied Statistics · September 1, 2023 Regression is the most widely used modeling tool in statistics. Quantile regression offers a strategy for enhancing the regression picture beyond cus-tomary mean regression. With time-series data, we move to quantile autore-gression and, finally, with spat ... Full text Cite

Data from: Mechanistic modeling of climate effects on redistribution and population growth in a community of fish species.

Dataset · August 29, 2023 Understanding community responses to climate is critical for anticipating the future impacts of global change. However, despite increased research efforts in this field, models that explicitly include important biological mechanisms are lacking. Quantifyin ... Full text Cite

Zero-Inflated Beta Distribution Regression Modeling

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · March 1, 2023 A frequent challenge encountered with ecological data is how to interpret, analyze, or model data having a high proportion of zeros. Much attention has been given to zero-inflated count data, whereas models for non-negative continuous data with an abundanc ... Full text Cite

Modeling Community Dynamics Through Environmental Effects, Species Interactions and Movement

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · March 1, 2023 Understanding how communities respond to environmental change is frustrated by the fact that both species interactions and movement affect biodiversity in unseen ways. To evaluate the contributions of species interactions on community growth, dynamic model ... Full text Cite

TIME-DISCRETIZATION APPROXIMATION ENRICHES CONTINUOUS-TIME DISCRETE-SPACE MODELS FOR ANIMAL MOVEMENT

Journal Article Annals of Applied Statistics · March 1, 2023 Continuous time discrete state models are a valuable tool for explaining animal movement. However, data collection to fit such models over a spec-ified window of time can be misaligned with the actual realization of the movement process. This necessitates ... Full text Cite

Kernel density estimation of conditional distributions to detect responses in satellite tag data

Journal Article Animal Biotelemetry · December 1, 2022 Background: As levels of anthropogenic noise in the marine environment rise, it is crucial to quantify potential associated effects on marine mammals. Yet measuring responses is challenging because most species spend the majority of their time submerged. C ... Full text Cite

Preferential sampling for bivariate spatial data

Journal Article Spatial Statistics · October 1, 2022 Preferential sampling provides a formal modeling specification to capture the effect of bias in a set of sampling locations on inference when a geostatistical model is used to explain observed responses at the sampled locations. In particular, it enables m ... Full text Cite

Spatio-temporal analysis of the extent of an extreme heat event

Journal Article Stochastic Environmental Research and Risk Assessment · September 1, 2022 Evidence of global warming induced from the increasing concentration of greenhouse gases in the atmosphere suggests more frequent warm days and heat waves. The concept of an extreme heat event (EHE), defined locally based on exceedance of a suitable local ... Full text Cite

Spatial Modeling of Day-Within-Year Temperature Time Series: An Examination of Daily Maximum Temperatures in Aragón, Spain

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · September 1, 2022 Acknowledging a considerable literature on modeling daily temperature data, we propose a multi-level spatiotemporal model which introduces several innovations in order to explain the daily maximum temperature in the summer period over 60 years in a region ... Full text Cite

SPATIAL FUNCTIONAL DATA MODELING OF PLANT REFLECTANCES

Journal Article Annals of Applied Statistics · September 1, 2022 Plant reflectance spectra, the profile of light reflected by leaves across different wavelengths, supply the spectral signature for a species at a spatial location to enable estimation of functional and taxonomic diversity for plants. We consider leaf spec ... Full text Cite

Spatial modeling for the distribution of species in plant communities

Journal Article Spatial Statistics · August 1, 2022 Species distribution modeling is a primary ecological activity that has witnessed substantial evolution since the turn of the 21st century. For plant communities, two key features are the move from individual to joint species modeling and the move from reg ... Full text Cite

Editorial: The impact of spatial statistics

Journal Article Spatial Statistics · August 1, 2022 Full text Cite

Approximate Bayesian inference for a spatial point process model exhibiting regularity and random aggregation

Journal Article Scandinavian Journal of Statistics · March 1, 2022 In this article, we propose a doubly stochastic spatial point process model with both aggregation and repulsion. This model combines the ideas behind Strauss processes and log Gaussian Cox processes. The likelihood for this model is not expressible in clos ... Full text Cite

Generalized Evolutionary Point Processes: Model Specifications and Model Comparison

Journal Article Methodology and Computing in Applied Probability · September 1, 2021 Generalized evolutionary point processes offer a class of point process models that allows for either excitation or inhibition based upon the history of the process. In this regard, we propose modeling which comprises generalization of the nonlinear Hawkes ... Full text Cite

Bayesian joint quantile autoregression

Generative spatial generalized dissimilarity mixed modelling (spGDMM): An enhanced approach to modelling beta diversity

Assessing space and time changes in daily maximum temperature in the Ebro basin (Spain) using model-based statistical tools

Space-time multi-level modeling for zooplankton abundance employing double data fusion and calibration

Mechanistic modeling of climate effects on redistribution and population growth in a community of fish species.

Joint multivariate and functional modeling for plant traits and reflectances

SPATIAL QUANTILE AUTOREGRESSION FOR SEASON WITHIN YEAR DAILY MAXIMUM TEMPERATURE DATA

Data from: Mechanistic modeling of climate effects on redistribution and population growth in a community of fish species.

Zero-Inflated Beta Distribution Regression Modeling

Modeling Community Dynamics Through Environmental Effects, Species Interactions and Movement

TIME-DISCRETIZATION APPROXIMATION ENRICHES CONTINUOUS-TIME DISCRETE-SPACE MODELS FOR ANIMAL MOVEMENT

Kernel density estimation of conditional distributions to detect responses in satellite tag data

Preferential sampling for bivariate spatial data

Spatio-temporal analysis of the extent of an extreme heat event

Spatial Modeling of Day-Within-Year Temperature Time Series: An Examination of Daily Maximum Temperatures in Aragón, Spain

SPATIAL FUNCTIONAL DATA MODELING OF PLANT REFLECTANCES

Spatial modeling for the distribution of species in plant communities

Editorial: The impact of spatial statistics

Journal Article Spatial Statistics · August 1, 2022 Full text Cite

Approximate Bayesian inference for a spatial point process model exhibiting regularity and random aggregation

Generalized Evolutionary Point Processes: Model Specifications and Model Comparison

Multivariate functional data modeling with time-varying clustering

Journal Article Test · September 1, 2021 We consider the setting of multivariate functional data collected over time at each of a set of sites. Our objective is to implement model-based clustering of the functions across the sites where we allow such clustering to vary over time. Anticipating dep ... Full text Cite

Modeling spatially biased citizen science effort through the eBird database

Journal Article Environmental and Ecological Statistics · September 1, 2021 Citizen science databases are increasing in importance as sources of ecological information, but variability in effort across locations is inherent to such data. Spatially biased data—data not sampled uniformly across the study region—is expected. A furthe ... Full text Cite

Assessing Disparity Using Measures of Racial and Educational Isolation.

Journal Article International journal of environmental research and public health · September 2021 We develop a local, spatial measure of educational isolation (EI) and characterize the relationship between EI and our previously developed measure of racial isolation (RI). EI measures the extent to which non-college educated individuals are exposed prima ... Full text Cite

Long-term spatial modelling for characteristics of extreme heat events

Journal Article Journal of the Royal Statistical Society. Series A: Statistics in Society · July 1, 2021 There is increasing evidence that global warming manifests itself in more frequent warm days and that heat waves will become more frequent. Presently, a formal definition of a heat wave is not agreed upon in the literature. To avoid this debate, we conside ... Full text Cite

Continuous-Time Discrete-State Modeling for Deep Whale Dives

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · June 1, 2021 Understanding unexposed/baseline behavior of marine mammals is required to assess the effects of increasing levels of anthropogenic noise exposure in the marine environment. However, quantifying variation in the baseline behavior of whales is challenging d ... Full text Cite

The role of odds ratios in joint species distribution modeling

Journal Article Environmental and Ecological Statistics · June 1, 2021 Joint species distribution modeling is attracting increasing attention these days, acknowledging the fact that individual level modeling fails to take into account expected dependence/interaction between species. These joint models capture species dependen ... Full text Cite

A Partition Dirichlet Process Model for Functional Data Analysis

Journal Article Sankhya B · May 1, 2021 Recently, extensions of the Dirichlet process to the functional domain have been presented in the literature. These processes can be classified based on the type of labeling they induce across different arguments in the domain, i.e., marginal or joint labe ... Full text Cite

Multivariate Spatial Process Models

Chapter · January 1, 2021 Spatially-referenced multivariate data is becoming increasingly common. Here, we focus on data in the form of vectors observed at a finite set of spatial locations. Regression models are of interest in order to explain the response vectors as well as to pr ... Full text Cite

Analyzing car thefts and recoveries with connections to modeling origin–destination point patterns

Journal Article Spatial Statistics · August 1, 2020 For a given region, we have a dataset composed of car theft locations along with a linked dataset of recovery locations which, due to partial recovery, is a relatively small subset of the set of theft locations. For an investigator seeking to understand th ... Full text Cite

Statistical challenges in spatial analysis of plant ecology data

Journal Article Spatial Statistics · June 1, 2020 The scope of spatial statistics problems arising in ecology is substantial. They concern both plant and animal behavior. Here, we discuss only plants. The range of issues is still very large and so we confine ourselves to four challenges, each within the c ... Full text Cite

Introduction to the special issue on frontiers in spatial research

Journal Article Spatial Statistics · June 1, 2020 Full text Cite

Spatial hedonic modelling adjusted for preferential sampling

Journal Article Journal of the Royal Statistical Society. Series A: Statistics in Society · January 1, 2020 Hedonic models are widely used to predict selling prices of properties. Originally, they were proposed as simple spatial regressions, i.e. a spatially referenced response regressed on spatially referenced predictors. Subsequently, spatial random effects we ... Full text Cite

Preferential sampling for presence/absence data and for fusion of presence/absence data with presence-only data

Journal Article Ecological Monographs · August 1, 2019 Presence/absence data and presence-only data are the two customary sources for learning about species distributions over a region. We present an ambitious agenda with regard to the analysis of such data. We illuminate the fundamental modeling differences b ... Full text Cite

Exploring geometric anisotropy for point-referenced spatial data

Journal Article Spatial Statistics · August 1, 2019 Isotropic covariance functions are routinely adopted in specifying models for point-referenced spatial data but carry the limitation that spatial dependence is not directional. Geometric anisotropic covariance functions offer a class of stationary specific ... Full text Cite

Disease Mapping With Generative Models

Journal Article American Statistician · July 3, 2019 Disease mapping focuses on learning about areal units presenting high relative risk. Disease mapping models assume that the disease counts are distributed as Poisson random variables with the respective means typically specified as the product of the relat ... Full text Cite

Pollution state modelling for Mexico City

Journal Article Journal of the Royal Statistical Society. Series A: Statistics in Society · June 1, 2019 Ground level ozone and particulate matter pollutants are associated with a variety of health issues and increased mortality. For this reason, Mexican environmental agencies regulate pollutant levels. In addition, Mexico City defines pollution emergencies b ... Full text Cite

Velocities for spatio-temporal point patterns

Journal Article Spatial Statistics · March 1, 2019 Point patterns gathered over space and time are receiving increasing attention in the literature. Examples include incidence of disease events, incidence of insurgent activity events, or incidence of crime events. Point pattern models can attempt to explai ... Full text Cite

Spatial Joint Species Distribution Modeling using Dirichlet Processes.

Journal Article Statistica Sinica · January 2019 Species distribution models usually attempt to explain presence-absence or abundance of a species at a site in terms of the environmental features (so-called abiotic features) present at the site. Historically, such models have considered species individua ... Full text Cite

Rejoinder on: Process modeling for slope and aspect with application to elevation data maps

Journal Article Test · December 1, 2018 Full text Cite

Process modeling for slope and aspect with application to elevation data maps

Journal Article Test · December 1, 2018 Learning about the behavior of land surface gradients and, in particular, slope and aspect over a region from a dataset of levels obtained at a set of (possibly) irregularly spaced locations assumes importance in a variety of applications. A primary exampl ... Full text Cite

Local real-time forecasting of ozone exposure using temperature data

Journal Article Environmetrics · November 1, 2018 Rigorous and rapid assessment of ambient ozone exposure is important for informing the public about ozone levels that may lead to adverse health effects. In this paper, we use hierarchical modeling to enable real-time forecasting of 8-hr average ozone expo ... Full text Cite

Joint Temporal Point Pattern Models for Proximate Species Occurrence in a Fixed Area Using Camera Trap Data

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · September 1, 2018 The distinction between an overlap in species daily activity patterns and proximate co-occurrence of species for a location and time due to behavioral attraction or avoidance is critical when addressing the question of species co-occurrence. We use data fr ... Full text Cite

Maximum weight matching using odd-sized cycles: Max-product belief propagation and half-integrality

Conference IEEE Transactions on Information Theory · March 1, 2018 We study the maximum weight matching (MWM) problem for general graphs through the max-product belief propagation (BP) and related Linear Programming (LP). The BP approach provides distributed heuristics for finding the maximum a posteriori (MAP) assignment ... Full text Cite

Assessing the joint behaviour of species traits as filtered by environment

Journal Article Methods in Ecology and Evolution · March 1, 2018 Understanding and predicting how species traits are shaped by prevailing environmental conditions is an important yet challenging task in ecology. Functional trait-based approaches can replace potentially idiosyncratic species-specific response models in l ... Full text Cite

Alternating Gaussian Process Modulated Renewal Processes for Modeling Threshold Exceedances and Durations.

Journal Article Stochastic environmental research and risk assessment : research journal · February 2018 It is often of interest to model the incidence and duration of threshold exceedance events for an environmental variable over a set of monitoring locations. Such data arrive over continuous time and can be considered as observations of a two-state process ... Full text Cite

Hierarchical spatio-temporal modeling of resting state fMRI data

Conference Springer Proceedings in Mathematics and Statistics · January 1, 2018 In recent years, state of the art brain imaging techniques like Functional Magnetic Resonance Imaging (fMRI), have raised new challenges to the statistical community, which is asked to provide new frameworks for modeling and data analysis. Here, motivated ... Full text Cite

Accommodating the ecological fallacy in disease mapping in the absence of individual exposures.

Journal Article Statistics in medicine · December 2017 In health exposure modeling, in particular, disease mapping, the ecological fallacy arises because the relationship between aggregated disease incidence on areal units and average exposure on those units differs from the relationship between the event of i ... Full text Open Access Cite

Analysis of residential property sales using space–time point patterns

Journal Article Spatial Statistics · August 1, 2017 Customarily, for housing markets, interest focuses on selling prices of properties at locations and times. Hedonic models are employed using property-level, neighborhood-level, and economic regressors. However, in hedonic modeling the fact that the locatio ... Full text Cite

Approximate Bayesian Computation and Model Assessment for Repulsive Spatial Point Processes

Journal Article Journal of Computational and Graphical Statistics · July 3, 2017 In many applications involving spatial point patterns, we find evidence of inhibition or repulsion. The most commonly used class of models for such settings are the Gibbs point processes. A recent alternative, at least to the statistical community, is the ... Full text Cite

Space and circular time log Gaussian Cox processes with application to crime event data

Journal Article Annals of Applied Statistics · June 1, 2017 We view the locations and times of a collection of crime events as a space–time point pattern. Then, with either a nonhomogeneous Poisson process or with a more general Cox process, we need to specify a space–time intensity. For the latter, we need a rando ... Full text Cite

Bayesian Modeling and Analysis of Geostatistical Data.

Journal Article Annual review of statistics and its application · March 2017 The most prevalent spatial data setting is, arguably, that of so-called geostatistical data, data that arise as random variables observed at fixed spatial locations. Collection of such data in space and in time has grown enormously in the past two decades. ... Full text Cite

Biomass prediction using a density-dependent diameter distribution model

Journal Article Annals of Applied Statistics · March 1, 2017 Prediction of aboveground biomass, particularly at large spatial scales, is necessary for estimating global-scale carbon sequestration. Since biomass can be measured only by sacrificing trees, total biomass on plots is never observed. Rather, allometric eq ... Full text Cite

Space-time modeling for post-fire vegetation recovery

Journal Article Stochastic Environmental Research and Risk Assessment · January 1, 2017 Recently, there has been increased interest in the behavior of wildfires. Behavior includes explaining: incidence of wildfires; recurrence times for wildfires; sizes, scars, and directions of wildfires; and recovery of burned regions after a wildfire. We s ... Full text Cite

Bayesian inference and model assessment for spatial point patterns using posterior predictive samples

Journal Article Bayesian Analysis · January 1, 2017 Spatial point pattern data describes locations of events observed over a given domain, with the number of and locations of these events being random. Historically, data analysis for spatial point patterns has focused on rejecting complete spatial randomnes ... Full text Cite

Joint species distribution modeling: Dimension reduction using Dirichlet processes

Journal Article Bayesian Analysis · January 1, 2017 Species distribution models are used to evaluate the variables that affect the distribution and abundance of species and to predict biodiversity. Historically, such models have been fitted to each species independently. While independent models can provide ... Full text Cite

The wrapped skew Gaussian process for analyzing spatio-temporal data

Journal Article Stochastic Environmental Research and Risk Assessment · December 1, 2016 We consider modeling of angular or directional data viewed as a linear variable wrapped onto a unit circle. In particular, we focus on the spatio-temporal context, motivated by a collection of wave directions obtained as computer model output developed dyn ... Full text Cite

Spatial statistics and Gaussian processes: A beautiful marriage

Journal Article Spatial Statistics · November 1, 2016 Spatial analysis has grown at a remarkable rate over the past two decades. Fueled by sophisticated GIS software and inexpensive and fast computation, collection of data with spatially referenced information has increased. Recognizing that such information ... Full text Cite

On nearest-neighbor Gaussian process models for massive spatial data.

Journal Article Wiley interdisciplinary reviews. Computational statistics · September 2016 Gaussian Process (GP) models provide a very flexible nonparametric approach to modeling location-and-time indexed datasets. However, the storage and computational requirements for GP models are infeasible for large spatial datasets. Nearest Neighbor Gaussi ... Full text Cite

Spatio-temporal circular models with non-separable covariance structure

Journal Article Test · June 1, 2016 Circular data arise in many areas of application. Recently, there has been interest in looking at circular data collected separately over time and over space. Here, we extend some of this work to the spatio-temporal setting, introducing space–time dependen ... Full text Cite

Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets

Journal Article Journal of the American Statistical Association · April 2, 2016 Spatial process models for analyzing geostatistical data entail computations that become prohibitive as the number of spatial locations become large. This article develops a class of highly scalable nearest-neighbor Gaussian process (NNGP) models to provid ... Full text Cite

Modeling change in forest biomass across the eastern US

Journal Article Environmental and Ecological Statistics · March 1, 2016 Predictions of above-ground biomass and the change in above-ground biomass require attachment of uncertainty due the range of reported predictions for forests. Because above-ground biomass is seldom measured, there have been no opportunities to obtain such ... Full text Cite

Joint Modeling of Climate Niches for Adult and Juvenile Trees

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · March 1, 2016 Typical ecological gradient analysis for plant species considers variation in the response along a gradient of covariate values, for example, temperature or precipitation. Response is customarily modeled through the presence/absence or a suitable measure o ... Full text Cite

Geographic segmentation via latent poisson factor model

Conference WSDM 2016 - Proceedings of the 9th ACM International Conference on Web Search and Data Mining · February 8, 2016 Discovering latent structures in spatial data is of critical importance to understanding the user behavior of locationbased services. In this paper, we study the problem of geographic segmentation of spatial data, which involves dividing a collection of ob ... Full text Cite

Spatial process gradients and their use in sensitivity analysis for environmental processes

Journal Article Journal of Statistical Planning and Inference · January 1, 2016 This paper develops methodology for local sensitivity analysis based on directional derivatives associated with spatial processes. Formal gradient analysis for spatial processes was elaborated in previous papers, focusing on distribution theory for directi ... Full text Cite

Markov-modulated marked poisson processes for check-in data

Conference 33rd International Conference on Machine Learning, ICML 2016 · January 1, 2016 We develop continuous-time probabilistic models to study trajectory data consisting of times and locations of user 'check-ins'. We model the data as realizations of a marked point process, with intensity and mark-distribution modulated by a latent Markov j ... Cite

A data fusion approach for spatial analysis of speciated PM2.5 across time

Journal Article Environmetrics · December 1, 2015 PM2.5 exposure is linked to a number of adverse health effects such as lung cancer and cardiovascular disease. However, PM2.5 is a complex mixture of different species whose composition varies substantially in both space and time. An open question is how t ... Full text Cite

Stochastic Modeling for Velocity of Climate Change

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · September 23, 2015 The velocity of climate change is defined as an instantaneous rate of change needed to maintain a constant climate. It is developed as the ratio of the temporal gradient of climate change over the spatial gradient of climate change. Ecologically, understan ... Full text Cite

Bayesian wombling: Finding rapid change in spatial maps

Journal Article Wiley Interdisciplinary Reviews: Computational Statistics · September 1, 2015 In spatial analysis, typically we specify a region of interest and consider a spatial surface over the region. It is often of interest to ascertain where the surface is changing rapidly. Identifying locations or curves where there is rapid change is referr ... Full text Cite

Using spatial gradient analysis to clarify species distributions with application to South African protea

Journal Article Journal of Geographical Systems · July 1, 2015 Typical ecological gradient analyses consider variation in the response of plants along a gradient of covariate values, but generally constrain themselves to predetermined response curves and ignore spatial autocorrelation. In this paper, we develop a form ... Full text Cite

Quantifying uncertainty for temperature maps derived from computer models

Journal Article Spatial Statistics · May 1, 2015 Computer models are often deterministic simulators used to predict several environmental phenomena. Such models do not associate any measure of uncertainty with their output since they are derived from deterministic specifications. However, many sources of ... Full text Cite

Comments on: Comparing and selecting spatial predictors using local criteria

Journal Article Test · March 1, 2015 Full text Cite

spBayes for large univariate and multivariate point-referenced spatio-temporal data models

Journal Article Journal of Statistical Software · January 1, 2015 In this paper we detail the reformulation and rewrite of core functions in the spBayes R package. These efforts have focused on improving computational efficiency, flexibility, and usability for point-referenced data models. Attention is given to algorithm ... Full text Cite

Joint spatio-temporal analysis of a linear and a directional variable: Space-time modeling of wave heights and wave directions in the adriatic sea

Journal Article Statistica Sinica · January 1, 2015 It is valuable to have a better understanding of factors that influence sea motion and to provide more accurate forecasts. In particular, we are motivated by data on wave heights and outgoing wave directions over a region in the Adriatic sea during the tim ... Full text Cite

Modeling individual tree growth by fusing diameter tape and increment core data

Journal Article Environmetrics · December 1, 2014 Tree growth estimation is a challenging task as difficulties associated with data collection and inference often result in inaccurate estimates. Two main methods for tree growth estimation are diameter tape measurements and increment cores. The former invo ... Full text Cite

On Covariate Importance for Regression Models with Multivariate Response

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · December 1, 2014 We address the question of identifying the relative importance of covariates for model response, a form of sensitivity analysis. Relative importance is typically implemented as part of the model building procedure, e.g., forward variable selection or backw ... Full text Cite

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores.

Journal Article Journal of the Royal Statistical Society. Series C, Applied statistics · November 2014 Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from ... Full text Cite

Modeling Space and Space-Time Directional Data Using Projected Gaussian Processes

Journal Article Journal of the American Statistical Association · October 2, 2014 Directional data naturally arise in many scientific fields, such as oceanography (wave direction), meteorology (wind direction), and biology (animal movement direction). Our contribution is to develop a fully model-based approach to capture structured spat ... Full text Cite

Explaining return times for wildfires

Journal Article Journal of Statistical Theory and Practice · July 3, 2014 Our interest is in analyzing fire regimes in the Mediterranean ecosystem in the Cape Floristic Region of South Africa (CFR). With this objective, we consider an extensive database of observed fires with high-resolution meteorological data during the period ... Full text Cite

More than the sum of the parts: forest climate response from joint species distribution models.

Journal Article Ecological applications : a publication of the Ecological Society of America · July 2014 The perceived threat of climate change is often evaluated from species distribution models that are fitted to many species independently and then added together. This approach ignores the fact that species are jointly distributed and limit one another. Spe ... Full text Cite

Imputation of confidential data sets with spatial locations using disease mapping models.

Journal Article Statistics in medicine · May 2014 Data that include fine geographic information, such as census tract or street block identifiers, can be difficult to release as public use files. Fine geography provides information that ill-intentioned data users can use to identify individuals. We propos ... Full text Cite

Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology.

Journal Article Global change biology · April 2014 Understanding the drivers of phenological events is vital for forecasting species' responses to climate change. We developed flexible Bayesian survival regression models to assess a 29-year, individual-level time series of flowering phenology from four tax ... Full text Cite

Modeling daily flowering probabilities: Expected impact of climate change on Japanese cherry phenology

Journal Article Global Change Biology · 2014 Cite

Modeling daily flowering probabilities: Expected impact of climate change on Japanese cherry phenology

Journal Article Global Change Biology · 2014 Cite

Assessing exceedance of ozone standards: A space-time downscaler for fourth highest ozone concentrations

Journal Article Environmetrics · January 1, 2014 The US Environmental Protection Agency is required to monitor, regulate, and set national ambient air quality standards for ozone. To investigate ozone exposure, the Environmental Protection Agency utilizes monitoring devices along with estimates of gridde ... Full text Cite

Bayesian nonparametric modeling for functional analysis of variance

Journal Article Annals of the Institute of Statistical Mathematics · January 1, 2014 Analysis of variance is a standard statistical modeling approach for comparing populations. The functional analysis setting envisions that mean functions are associated with the populations, customarily modeled using basis representations, and seeks to com ... Full text Cite

Dual impacts of climate change: forest migration and turnover through life history.

Journal Article Global change biology · January 2014 Tree species are predicted to track future climate by shifting their geographic distributions, but climate-mediated migrations are not apparent in a recent continental-scale analysis. To better understand the mechanisms of a possible migration lag, we anal ... Full text Cite

Process modeling for soil moisture using sensor network data

Journal Article Statistical Methodology · January 1, 2014 The quantity of water contained in soil is referred to as the soil moisture. Soil moisture plays an important role in agriculture, percolation, and soil chemistry. Precipitation, temperature, atmospheric demand and topography are the primary processes that ... Full text Cite

Belief propagation for linear programming

Conference IEEE International Symposium on Information Theory - Proceedings · December 19, 2013 Belief Propagation (BP) is a popular, distributed heuristic for performing MAP computations in Graphical Models. BP can be interpreted, from a variational perspective, as minimizing the Bethe Free Energy (BFE). BP can also be used to solve a special class ... Full text Cite

Scaling integral projection models for analyzing size demography

Journal Article Statistical Science · November 1, 2013 Historically, matrix projection models (MPMs) have been employed to study population dynamics with regard to size, age or structure. To work with continuous traits, in the past decade, integral projection models (IPMs) have been proposed. Following the pat ... Full text Cite

Synthesizing categorical datasets to enhance inference

Journal Article Statistical Methodology · November 1, 2013 A common data analysis setting consists of a collection of datasets of varying sizes that are all relevant to a particular scientific question, but which include different subsets of the relevant variables, presumably with some overlap. Here, we demonstrat ... Full text Cite

Spatial Regression Modeling for Compositional Data With Many Zeros

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · September 1, 2013 Compositional data analysis considers vectors of nonnegative-valued variables subject to a unit-sum constraint. Our interest lies in spatial compositional data, in particular, land use/land cover (LULC) data in the northeastern United States. Here, the obs ... Full text Cite

Analyzing first flowering event data using survival models with space and time-varying covariates

Journal Article Environmetrics · August 1, 2013 First flowering events in cherry trees are believed to be closely related to temperature patterns during the winter and spring months. Earlier works have incorporated the idea of temperature thresholds, defining chill and heat functions based on these thre ... Full text Cite

Directional data analysis under the general projected normal distribution.

Journal Article Statistical methodology · July 2013 The projected normal distribution is an under-utilized model for explaining directional data. In particular, the general version provides flexibility, e.g., asymmetry and possible bimodality along with convenient regression specification. Here, we clarify ... Full text Cite

Spatio-temporal modeling for real-time ozone forecasting.

Journal Article Spatial statistics · May 2013 The accurate assessment of exposure to ambient ozone concentrations is important for informing the public and pollution monitoring agencies about ozone levels that may lead to adverse health effects. High-resolution air quality information can offer signif ... Full text Cite

Spatial interaction models with individual-level data for explaining labor flows and developing local labor markets

Journal Article Computational Statistics and Data Analysis · February 1, 2013 As a result of increased mobility patterns of workers, explaining labor flows and partitioning regions into local labor markets (LLMs) have become important economic issues. For the former, it is useful to understand jointly where individuals live and wher ... Full text Cite

Bayesian nonparametric modeling for functional analysis of variance

Journal Article Annals of the Institute of Statistical Mathematics · 2013 Cite

Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation

Journal Article Landscape Ecology · January 1, 2013 Woody invasive plants are an increasing component of the New England flora. Their success and geographic spread are mediated in part by landscape characteristics. We tested whether woody invasive plant richness was higher in landscapes with many forest edg ... Full text Cite

A graphical transformation for belief propagation: Maximum Weight Matchings and odd-sized cycles

Conference Advances in Neural Information Processing Systems · January 1, 2013 Max-product 'belief propagation' (BP) is a popular distributed heuristic for finding the Maximum A Posteriori (MAP) assignment in a joint probability distribution represented by a Graphical Model (GM). It was recently shown that BP converges to the correct ... Cite

Loop calculus and bootstrap-belief propagation for perfect matchings on arbitrary graphs

Conference Journal of Physics: Conference Series · January 1, 2013 This manuscript discusses computation of the Partition Function (PF) and the Minimum Weight Perfect Matching (MWPM) on arbitrary, non-bipartite graphs. We present two novel problem formulations-one for computing the PF of a Perfect Matching (PM) and one fo ... Full text Cite

Spatial misalignment models for small area estimation: A simulation study

Chapter · January 1, 2013 We propose a class of misaligned data models for addressing typical small area estimation (SAE) problems. In particular, we extend hierarchical Bayesian atom-based models for spatial misalignment to the SAE context enabling use of auxiliary covariates, whi ... Full text Cite

Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation

Journal Article Landscape Ecology · 2013 Cite

Generalized belief propagation on tree robust structured region graphs

Conference Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, UAI 2012 · December 1, 2012 This paper provides some new guidance in the construction of region graphs for Generalized Belief Propagation (GBP). We connect the problem of choosing the outer regions of a Loop- Structured Region Graph (SRG) to that of finding a fundamental cycle basis ... Cite

A cluster-cumulant expansion at the fixed points of belief propagation

Conference Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, UAI 2012 · December 1, 2012 We introduce a new cluster-cumulant expansion (CCE) based on the fixed points of iterative belief propagation (IBP). This expansion is similar in spirit to the loop-series (LS) recently introduced in [1]. However, in contrast to the latter, the CCE enjoys ... Cite

Rejoinder

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · December 1, 2012 Full text Cite

Inference for Size Demography from Point Pattern Data using Integral Projection Models.

Journal Article Journal of agricultural, biological, and environmental statistics · December 2012 Population dynamics with regard to evolution of traits has typically been studied using matrix projection models (MPMs). Recently, to work with continuous traits, integral projection models (IPMs) have been proposed. Imitating the path with MPMs, IPMs are ... Full text Cite

Kernel Averaged Predictors for Spatio-Temporal Regression Models.

Journal Article Spatial statistics · December 2012 In applications where covariates and responses are observed across space and time, a common goal is to quantify the effect of a change in the covariates on the response while adequately accounting for the spatio-temporal structure of the observations. The ... Full text Cite

On the Effect of Preferential Sampling in Spatial Prediction.

Journal Article Environmetrics · November 2012 The choice of the sampling locations in a spatial network is often guided by practical demands. In particular, many locations are preferentially chosen to capture high values of a response, for example, air pollution levels in environmental monitoring. The ... Full text Cite

Spatial Design for Knot Selection in Knot-Based Dimension Reduction Models

Chapter · October 11, 2012 This chapter addresses the settings where there is need to specify knots in order to fit desired spatial models. That is, it seeks to fit hierarchical models in order to enable full inference and to adequately capture uncertainty. The chapter adopts an app ... Full text Cite

Rejoinder

Journal Article Bayesian Analysis · September 10, 2012 Full text Cite

The k-ZIG: flexible modeling for zero-inflated counts.

Journal Article Biometrics · September 2012 Many applications involve count data from a process that yields an excess number of zeros. Zero-inflated count models, in particular, zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models, along with Poisson hurdle models, are commo ... Full text Cite

Space-time data fusion under error in computer model output: an application to modeling air quality.

Journal Article Biometrics · September 2012 We provide methods that can be used to obtain more accurate environmental exposure assessment. In particular, we propose two modeling approaches to combine monitoring data at point level with numerical model output at grid cell level, yielding improved pre ... Full text Cite

Process modelling for contingency tables with ordered categories

Journal Article Statistical Modelling · June 1, 2012 We consider the setting of a multi-way contingency table with ordinal classifications. The contribution of this paper is to propose a joint probability model for the uncensored variables that is apart from the imposed categorization. Specifically, for an m ... Full text Cite

Spatial Quantile Multiple Regression Using the Asymmetric Laplace Process

Journal Article Bayesian Analysis · June 1, 2012 Full text Cite

Hierarchical Modeling for Spatial Data Problems.

Journal Article Spatial statistics · May 2012 This short paper is centered on hierarchical modeling for problems in spatial and spatio-temporal statistics. It draws its motivation from the interdisciplinary research work of the author in terms of applications in the environmental sciences - ecological ... Full text Cite

Maternal age, birth order, and race: differential effects on birthweight.

Journal Article J Epidemiol Community Health · February 2012 BACKGROUND: Studies examining the influence of maternal age and birth order on birthweight have not effectively disentangled the relative contributions of each factor to birthweight, especially as they may differ by race. METHODS: A population-based, cross ... Full text Link to item Cite

Spatial analysis of wave direction data using wrapped Gaussian processes

Journal Article Annals of Applied Statistics · January 1, 2012 Directional data arise in various contexts such as oceanography (wave directions) and meteorology (wind directions), as well as with measurements on a periodic scale (weekdays, hours, etc.). Our contribution is to introduce a model-based approach to handle ... Full text Cite

Attaching uncertainty to deterministic spatial interpolations

Journal Article Statistical Methodology · January 1, 2012 Deterministic spatial interpolation algorithms such as the natural neighbor interpolation (NNI) or the Cressman interpolation schemes are widely used to interpolate environmental features. In particular, the former have been applied to digital elevation mo ... Full text Cite

Bayesian dynamic modeling for large space-time datasets using Gaussian predictive processes

Journal Article Journal of Geographical Systems · January 1, 2012 In this paper, we extend the applicability of a previously proposed class of dynamic space-time models by enabling them to accommodate large datasets. We focus on the common setting where space is viewed as continuous but time is taken to be discrete. Scal ... Full text Cite

Integrating local classifiers through nonlinear dynamics on label graphs with an application to image segmentation

Conference Proceedings of the IEEE International Conference on Computer Vision · December 1, 2011 We present a new method to combine possibly inconsistent locally (piecewise) trained conditional models p(y αx α) into pseudo-samples from a global model. Our method does not require training of a CRF, but instead generates samples by iterating forward a w ... Full text Cite

A Spatial Measure of Neighborhood Level Racial Isolation Applied to Low Birthweight, Preterm Birth, and Birthweight in North Carolina

Journal Article Spatial and Spatio-temporal Epidemiology · December 2011 Cite

Adaptive Gaussian Predictive Process Models for Large Spatial Datasets.

Journal Article Environmetrics · December 2011 Large point referenced datasets occur frequently in the environmental and natural sciences. Use of Bayesian hierarchical spatial models for analyzing these datasets is undermined by onerous computational burdens associated with parameter estimation. Low-ra ... Full text Cite

Pushing the power of stochastic greedy ordering schemes for inference in graphical models

Conference Proceedings of the National Conference on Artificial Intelligence · November 2, 2011 We study iterative randomized greedy algorithms for generating (elimination) orderings with small induced width and state space size - two parameters known to bound the complexity of inference in graphical models. We propose and implement the Iterative Gre ... Cite

Stopping rules for randomized greedy triangulation schemes

Conference Proceedings of the National Conference on Artificial Intelligence · November 2, 2011 Many algorithms for performing inference in graphical models have complexity that is exponential in the treewidth - a parameter of the underlying graph structure. Computing the (minimal) treewidth is NP-complete, so stochastic algorithms are sometimes used ... Cite

Local linear suppression for wireless sensor network data

Journal Article Brazilian Journal of Probability and Statistics · November 1, 2011 With wireless sensor networks, preserving battery life is critical. For such sensors, data collection is relatively cheap while data transmission is relatively expensive. For such networks in ecological settings, certain processes are sufficiently predicta ... Full text Cite

Corrigendum to "A Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation" [Ecol. Modell. 221 (January (1)) (2010) 106-112]

Journal Article Ecological Modelling · September 24, 2011 Full text Cite

Inferential ecosystem models, from network data to prediction.

Journal Article Ecological applications : a publication of the Ecological Society of America · July 2011 Recent developments suggest that predictive modeling could begin to play a larger role not only for data analysis, but also for data collection. We address the example of efficient wireless sensor networks, where inferential ecosystem models can be used to ... Full text Cite

Hierarchical spatial modeling of uncertainty in air pollution and birth weight study.

Journal Article Statistics in medicine · July 2011 In environmental health studies air pollution measurements from the closest monitor are commonly used as a proxy for personal exposure. This technique assumes that air pollution concentrations are spatially homogeneous in the neighborhoods associated with ... Full text Cite

The dirichlet labeling process for clustering functional data

Journal Article Statistica Sinica · July 1, 2011 We consider problems involving functional data where we have a collection of functions, each viewed as a process realization, e.g., a random curve or surface. For a particular process realization, we assume that the observation at a given location can be a ... Full text Cite

Spatial Regression Using Kernel Averaged Predictors

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · June 9, 2011 Traditional spatial linear regression models assume that the mean of the response is a linear combination of predictors measured at the same location as the response. In spatial applications, however, it seems plausible that neighboring predictors can also ... Full text Cite

On the use of a PM(2.5) exposure simulator to explain birthweight.

Journal Article Environmetrics · June 2011 In relating pollution to birth outcomes, maternal exposure has usually been described using monitoring data. Such characterization provides a misrepresentation of exposure as it (i) does not take into account the spatial misalignment between an individual' ... Full text Cite

Spatial modeling for groundwater arsenic levels in North Carolina.

Journal Article Environmental science & technology · June 2011 To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic informat ... Full text Cite

SPATIAL ADJUSTMENT OF MEASUREMENT ERROR IN MATERNAL EXPOSURE TO AIR POLLUTION.

Conference AMERICAN JOURNAL OF EPIDEMIOLOGY · June 1, 2011 Link to item Cite

Scaling up: Linking field data and remote sensing with a hierarchical model

Journal Article International Journal of Geographical Information Science · March 1, 2011 Ecologists often seek to understand patterns and processes across multiple spatial and temporal scales ranging from centimeters to hundreds of meters and from seconds to years. Hierarchical statistical models offer a framework for sampling design and analy ... Full text Cite

Discussion on "Spatial prediction in the presence of positional error"

Journal Article Environmetrics · March 1, 2011 Full text Cite

Point pattern modelling for degraded presence-only data over large regions

Journal Article Journal of the Royal Statistical Society. Series C: Applied Statistics · January 1, 2011 Explaining the distribution of a species by using local environmental features is a long-standing ecological problem. Often, available data are collected as a set of presence locations only, thus precluding the possibility of a desired presence-absence ana ... Full text Cite

On herding and the perceptron cycling theorem

Conference Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010 · December 1, 2010 The paper develops a connection between traditional perceptron algorithms and recently introduced herding algorithms. It is shown that both algorithms can be viewed as an application of the perceptron cycling theorem. This connection strengthens some herdi ... Cite

A bivariate space-time downscaler under space and time misalignment.

Journal Article The annals of applied statistics · December 2010 Ozone and particulate matter PM(2.5) are co-pollutants that have long been associated with increased public health risks. Information on concentration levels for both pollutants come from two sources: monitoring sites and output from complex numerical mode ... Full text Cite

Analyzing spatial point patterns subject to measurement error

Journal Article Bayesian Analysis · December 1, 2010 We address the issue of inference for a noisy point pattern. The unobserved true point process is modelled as a nonhomogeneous Poisson process. For modeling the underlying intensity surface we use a scaled Gaussian mixture distribution. The noise that cree ... Full text Cite

Modeling large scale species abundance with latent spatial processes

Journal Article Annals of Applied Statistics · September 1, 2010 Modeling species abundance patterns using local environmental features is an important, current problem in ecology. The Cape Floristic Region (CFR) in South Africa is a global hot spot of diversity and endemism, and provides a rich class of species abundan ... Full text Cite

Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models.

Journal Article Statistics in medicine · July 2010 Birthweight and gestational age are closely related and represent important indicators of a healthy pregnancy. Customary modeling for birthweight is conditional on gestational age. However, joint modeling directly addresses the relationship between gestati ... Full text Cite

A Spatio-Temporal Downscaler for Output From Numerical Models.

Journal Article Journal of agricultural, biological, and environmental statistics · June 2010 Often, in environmental data collection, data arise from two sources: numerical models and monitoring networks. The first source provides predictions at the level of grid cells, while the second source gives measurements at points. The first is characteriz ... Full text Cite

HIERARCHICAL SPATIAL MODELING OF UNCERTAINTY IN AIR POLLUTION AND BIRTH WEIGHT STUDY

Conference AMERICAN JOURNAL OF EPIDEMIOLOGY · June 1, 2010 Link to item Cite

Latent Stick-Breaking Processes.

Journal Article Journal of the American Statistical Association · April 2010 We develop a model for stochastic processes with random marginal distributions. Our model relies on a stick-breaking construction for the marginal distribution of the process, and introduces dependence across locations by using a latent Gaussian copula mod ... Full text Open Access Cite

Continuous spatial process models for spatial extreme values

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · January 28, 2010 We propose a hierarchical modeling approach for explaining a collection of point-referenced extreme values. In particular, annual maxima over space and time are assumed to follow generalized extreme value (GEV) distributions, with parameters μ, σ, and ξ sp ... Full text Cite

A Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation

Journal Article Ecological Modelling · January 10, 2010 In this study we combined an extensive database of observed wildfires with high-resolution meteorological data to build a novel spatially and temporally varying survival model to analyze fire regimes in the Mediterranean ecosystem in the Cape Floristic Reg ... Full text Cite

Beem : BBucket Elimination with external memory

Conference Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010 · January 1, 2010 A major limitation of exact inference algorithms for probabilistic graphical models is their extensive memory usage, which often puts real-world problems out of their reach. In this paper we show how we can extend inference algorithms, particularly Bucket ... Cite

Disaggregated spatial modelling for areal unit categorical data.

Journal Article Journal of the Royal Statistical Society. Series C, Applied statistics · January 2010 We consider joint spatial modelling of areal multivariate categorical data assuming a multiway contingency table for the variables, modelled by using a log-linear model, and connected across units by using spatial random effects. With no distinction regard ... Full text Cite

Disparities in maternal hypertension and pregnancy outcomes: evidence from North Carolina, 1994-2003.

Journal Article Public Health Rep · 2010 OBJECTIVES: To better understand disparities in pregnancy outcomes, we analyzed data from North Carolina to determine how the pattern of maternal hypertensive disorders differs among non-Hispanic white (NHW), non-Hispanic black (NHB), and Hispanic women ac ... Full text Link to item Cite

Analyzing space-time sensor network data under suppression and failure in transmission

Journal Article Statistics and Computing · January 1, 2010 In this paper we present a fully model-based analysis of the effects of suppression and failure in data transmission with sensor networks. Sensor networks are becoming an increasingly common data collection mechanism in a variety of fields. Sensors can be ... Full text Cite

Fusing point and areal level space-time data with application to wet deposition

Journal Article Journal of the Royal Statistical Society. Series C: Applied Statistics · January 1, 2010 Motivated by the problem of predicting chemical deposition in eastern USA at weekly, seasonal and annual scales, the paper develops a framework for joint modelling of point- and grid-referenced spatiotemporal data in this context. The hierarchical model pr ... Full text Cite

Modeling space-time data using stochastic differential equations

Journal Article Bayesian Analysis · December 1, 2009 This paper demonstrates the use and value of stochastic differential equations for modeling space-time data in two common settings. The first consists of point-referenced or geostatistical data where observations are collected at fixed locations and times. ... Full text Cite

Performance evaluation of decentralized estimation systems with uncertain communication

Conference 2009 12th International Conference on Information Fusion, FUSION 2009 · November 18, 2009 An approach for evaluating the performance of decentralized estimation systems under non-ideal communi-cations is presented. Recent studies have shown that trans-mission disruptions occur frequently in tactical wireless net-works due to a variety of unpred ... Cite

Hybrid dirichlet mixture models for functional data

Journal Article Journal of the Royal Statistical Society. Series B: Statistical Methodology · September 1, 2009 In functional data analysis, curves or surfaces are observed, up to measurement error, at a finite set of locations, for, say, a sample of n individuals. Often, the curves are homogeneous, except perhaps for individual-specific regions that provide heterog ... Full text Cite

Improving the performance of predictive process modeling for large datasets.

Journal Article Computational statistics & data analysis · June 2009 Advances in Geographical Information Systems (GIS) and Global Positioning Systems (GPS) enable accurate geocoding of locations where scientific data are collected. This has encouraged collection of large spatial datasets in many fields and has generated co ... Full text Cite

A NEIGHBORHOOD AND SPATIAL MEASURE OF RACIAL ISOLATION APPLIED TO BIRTHWEIGHT.

Conference AMERICAN JOURNAL OF EPIDEMIOLOGY · June 1, 2009 Link to item Cite

Bayesian Nonparametric Functional Data Analysis Through Density Estimation.

Journal Article Biometrika · January 2009 In many modern experimental settings, observations are obtained in the form of functions, and interest focuses on inferences on a collection of such functions. We propose a hierarchical model that allows us to simultaneously estimate multiple curves nonpar ... Full text Cite

Hierarchical modeling for extreme values observed over space and time

Journal Article Environmental and Ecological Statistics · January 1, 2009 We propose a hierarchical modeling approach for explaining a collection of spatially referenced time series of extreme values. We assume that the observations follow generalized extreme value (GEV) distributions whose locations and scales are jointly spati ... Full text Cite

Interpreting self-organizing maps through space-time data models

Journal Article Annals of Applied Statistics · December 1, 2008 Self-organizing maps (SOMs) are a technique that has been used with high-dimensional data vectors to develop an archetypal set of states (nodes) that span, in some sense, the high-dimensional space. Noteworthy applications include weather states as describ ... Full text Cite

ANALYSIS OF MINNESOTA COLON AND RECTUM CANCER POINT PATTERNS WITH SPATIAL AND NONSPATIAL COVARIATE INFORMATION.

Journal Article The annals of applied statistics · October 2008 Colon and rectum cancer share many risk factors, and are often tabulated together as "colorectal cancer" in published summaries. However, recent work indicating that exercise, diet, and family history may have differential impacts on the two cancers encour ... Full text Cite

The nested Dirichlet process: Rejoinder

Journal Article Journal of the American Statistical Association · September 1, 2008 Full text Cite

Gaussian predictive process models for large spatial data sets.

Journal Article Journal of the Royal Statistical Society. Series B, Statistical methodology · September 2008 With scientific data available at geocoded locations, investigators are increasingly turning to spatial process models for carrying out statistical inference. Over the last decade, hierarchical models implemented through Markov chain Monte Carlo methods ha ... Full text Cite

Advanced algorithms for distributed fusion

Conference Proceedings of SPIE - The International Society for Optical Engineering · June 5, 2008 The US Military has been undergoing a radical transition from a traditional "platform-centric" force to one capable of performing in a "Network-Centric" environment. This transformation will place all of the data needed to efficiently meet tactical and str ... Full text Cite

Joint modeling of sensitivity and specificity.

Journal Article Statistics in medicine · May 2008 Sensitivity and specificity are two customary performance measures associated with medical diagnostic tests. Typically, they are modeled independently as a function of risk factors using logistic regression, which provides estimated functions for these pro ... Full text Cite

Modeling mercury deposition through latent space-time processes.

Journal Article Journal of the Royal Statistical Society. Series C, Applied statistics · April 2008 This paper provides a space-time process model for total wet mercury deposition. Key methodological features introduced include direct modeling of deposition rather than of expected deposition, the utilization of precipitation information (there is no depo ... Full text Cite

Modeling disease incidence data with spatial and spatio temporal dirichlet process mixtures.

Journal Article Biometrical journal. Biometrische Zeitschrift · February 2008 Disease incidence or mortality data are typically available as rates or counts for specified regions, collected over time. We propose Bayesian nonparametric spatial modeling approaches to analyze such data. We develop a hierarchical specification using spa ... Full text Cite

The nested dirichlet process

Journal Article Journal of the American Statistical Association · January 1, 2008 In multicenter studies, subjects in different centers may have different outcome distributions. This article is motivated by the problem of nonparametric modeling of these distributions, borrowing information across centers while also allowing centers to b ... Full text Cite

Introduction of the hybrid inference tool (HIT)

Conference FUSION 2007 - 2007 10th International Conference on Information Fusion · December 1, 2007 The construction of belief networks is a widely used methodology for high level fusion modeling. While some of the components of a belief network deal with ambiguous (probabilistic) data, others may deal with vague (possibilistic) data. Given the need to r ... Full text Cite

Generalized spatial dirichlet process models

Journal Article Biometrika · December 1, 2007 Many models for the study of point-referenced data explicitly introduce spatial random effects to capture residual spatial association. These spatial effects are customarily modelled as a zero-mean stationary Gaussian process. The spatial Dirichlet process ... Full text Cite

Data-driven processing in sensor networks

Conference CIDR 2007 - 3rd Biennial Conference on Innovative Data Systems Research · December 1, 2007 Wireless sensor networks are poised to enable continuous data collection on unprecedented scales, in terms of area location and size, and frequency. This is a great boon to fields such as ecological modeling. We are collaborating with researchers to build ... Cite

Statistical comparison of a hybrid approach with approximate and exact inference models for fusion 2+

Conference Proceedings of SPIE - The International Society for Optical Engineering · November 15, 2007 One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inferenc ... Full text Cite

Hierarchical spatial modeling for estimation of population size

Journal Article Environmental and Ecological Statistics · September 1, 2007 Estimation of population size has traditionally been viewed from a finite population sampling perspective. Typically, the objective is to obtain an estimate of the total population count of individuals within some region. Often, some stratification scheme ... Full text Cite

Guest Editorial: Spatial and spatio-temporal modeling in environmental and ecological statistics

Journal Article Environmental and Ecological Statistics · September 1, 2007 Full text Cite

Multilevel modeling using spatial processes: Application to the Singapore housing market

Journal Article Computational Statistics and Data Analysis · April 1, 2007 Customary spatial modeling with point-referenced data introduces a modeling specification that includes a mean term, a spatial error or random effects term and a pure error term. The spatial random effects are usually modeled through a mean zero spatial pr ... Full text Cite

Performance assessment for radiologists interpreting screening mammography.

Journal Article Statistics in medicine · March 2007 When interpreting screening mammograms radiologists decide whether suspicious abnormalities exist that warrant the recall of the patient for further testing. Previous work has found significant differences in interpretation among radiologists; their false- ... Full text Cite

Multivariate spatial modeling for geostatistical data using convolved covariance functions

Journal Article Mathematical Geology · February 1, 2007 Soil pollution data collection typically studies multivariate measurements at sampling locations, e.g., lead, zinc, copper or cadmium levels. With increased collection of such multivariate geostatistical spatial data, there arises the need for flexible exp ... Full text Cite

Suppression and failures in sensor networks: A Bayesian approach

Conference 33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings · January 1, 2007 Sensor networks allow continuous data collection on unprecedented scales. The primary limiting factor of such networks is energy, of which communication is the dominant consumer. The default strategy of nodes continually reporting their data to the root re ... Cite

From data reverence to data relevance: Model-mediated wireless sensing of the physical environment

Conference Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2007 Wireless sensor networks can be viewed as the integration of three subsystems: a low-impact in situ data acquisition and collection system, a system for inference of process models from observed data and a priori information, and a system that controls the ... Full text Cite

High Resolution Space-Time Ozone Modeling for Assessing Trends.

Journal Article Journal of the American Statistical Association · January 2007 The assessment of air pollution regulatory programs designed to improve ground level ozone concentrations is a topic of considerable interest to environmental managers. To aid this assessment, it is necessary to model the space-time behavior of ozone for p ... Full text Cite

Model fitting and inference under Latent Equilibrium Processes.

Journal Article Statistics and computing · January 2007 This paper presents a methodology for model fitting and inference in the context of Bayesian models of the type f(Y | X, theta)f(X | theta)f(theta), where Y is the (set of) observed data, theta is a set of model parameters and X is an unobserved (latent) s ... Full text Cite

Making Sense of Suppressions and Failures in Sensor Data: A Bayesian Approach.

Conference VLDB · 2007 Cite

Explaining species distribution patterns through hierarchical modeling

Journal Article Bayesian Analysis · December 1, 2006 Understanding spatial patterns of species diversity and the distributions of individual species is a consuming problem in biogeography and conservation. The Cape Floristic Region (CFR) of South Africa is a global hotspot of diversity and endemism, and the ... Full text Cite

Rejoinder

Journal Article Bayesian Analysis · December 1, 2006 Full text Cite

Bayesian Wombling: Curvilinear Gradient Assessment Under Spatial Process Models.

Journal Article Journal of the American Statistical Association · December 2006 Large-scale inference for random spatial surfaces over a region using spatial process models has been well studied. Under such models, local analysis of the surface (e.g., gradients at given points) has received recent attention. A more ambitious objective ... Full text Cite

Estimating measures of diagnostic accuracy when some covariate information is missing.

Journal Article Statistics in medicine · September 2006 Many biomedical data sets are concerned with relating the result of screening procedure(s) for a clinical event to the occurrence of that event. The effect of risk factors on measures of accuracy such as positive predictive value and negative predictive va ... Full text Cite

A future for models and data in environmental science.

Journal Article Trends in ecology & evolution · July 2006 Together, graphical models and the Bayesian paradigm provide powerful new tools that promise to change the way that environmental science is done. The capacity to merge theory with mechanistic understanding and empirical evidence, to assimilate diverse sou ... Full text Cite

Approximately optimal spatial design approaches for environmental health data

Journal Article Environmetrics · June 1, 2006 Environmental health research considers the relationship between exposures to environmental contaminants and particular health endpoints. Due to spatial structure associated with either exposures or outcomes, spatial modeling is making rapid inroads in env ... Full text Cite

Smoothness properties and gradient analysis under spatial Dirichlet process models

Journal Article Methodology and Computing in Applied Probability · June 1, 2006 When analyzing point-referenced spatial data, interest will be in the first order or global behavior of associated surfaces. However, in order to better understand these surfaces, we may also be interested in second order or local behavior, e.g., in the ra ... Full text Cite

Spatio-temporal modeling of fine particulate matter

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · March 1, 2006 Studies indicate that even short-term exposure to high concentrations of fine atmospheric particulate matter (PM2.5) can lead to long-term health effects. In this article, we propose a random effects model for PM2.5 concentrations. In particular, we antici ... Full text Cite

Building Statistical Models to Analyze Species Distributions

Journal Article Ecological Applications · 2006 Cite

Model-driven dynamic control of embedded wireless sensor networks

Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2006 Next-generation wireless sensor networks may revolutionize understanding of environmental change by assimilating heterogeneous data, assessing the relative value and costs of data collection, and scheduling activities accordingly. Thus, they are dynamic, d ... Full text Cite

Modelling map positional error to infer true feature location

Journal Article Canadian Journal of Statistics · January 1, 2006 The authors consider the issue of map positional error, or the difference between location as represented in a spatial database (i.e., a map) and the corresponding unobservable true location. They propose a fully model-based approach that incorporates aspe ... Full text Cite

Examining accuracy of screening mammography using an event order model.

Journal Article Statistics in medicine · January 2006 Screening mammography is a widely used method for breast cancer detection. For each mammogram we propose a performance model based on order of outcomes. That is, we envision an initial assessment, a follow up assessment if the initial one is positive and, ... Full text Cite

Gradients in spatial response surfaces with application to urban land values

Journal Article Journal of Business and Economic Statistics · January 1, 2006 For point-referenced spatial data, we often create explanatory models that introduce regression structure with error consisting of a spatial term and a white noise term. Here we consider more flexible regression structures that allow spatially varying regr ... Full text Cite

Bayesian nonparametric spatial modeling with dirichlet process mixing

Journal Article Journal of the American Statistical Association · September 1, 2005 Customary modeling for continuous point-referenced data assumes a Gaussian process that is often taken to be stationary. When such models are fitted within a Bayesian framework, the unknown parameters of the process are assumed to be random, so a random Ga ... Full text Cite

Bivariate spatial process modeling for constructing indicator or intensity weighted spatial CDFs

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · September 1, 2005 A spatial cumulative distribution function (SCDF) gives the proportion of a spatial domain D having the value of some response variable less than a particular level w. This article provides a fully hierarchical approach to SCDF modeling, using a Bayesian f ... Full text Cite

Spatial process modelling for univariate and multivariate dynamic spatial data

Journal Article Environmetrics · August 1, 2005 There is a considerable literature in spatiotemporal modelling. The approach adopted here applies to the setting where space is viewed as continuous but time is taken to be discrete. We view the data as a time series of spatial processes and work in the se ... Full text Cite

Tropical deforestation in Madagascar: Analysis using hierarchical, spatially explicit, Bayesian regression models

Journal Article Ecological Modelling · June 10, 2005 Establishing cause-effect relationships for deforestation at various scales has proven difficult even when rates of deforestation appear well documented. There is a need for better explanatory models, which also provide insight into the process of deforest ... Full text Cite

On model expansion, model contraction, identifiability and prior Information: Two illustrative scenarios involving mismeasured variables

Journal Article Statistical Science · May 1, 2005 When a candidate model for data is nonidentifiable, conventional wisdom dictates that the model must be simplified somehow so as to gain identifiability. We explore two scenarios involving mismeasured variables where, in fact, model expansion, as opposed t ... Full text Cite

On model expansion, model contraction, identifiability and prior information: Two illustrative scenarios involving mismeasured variables - Comment

Journal Article STATISTICAL SCIENCE · May 1, 2005 Link to item Cite

Spatio-temporal change-point modeling

Journal Article Journal of Statistical Planning and Inference · March 1, 2005 There is by now a substantial literature on spatio-temporal modeling. However, to date, there exists essentially no literature which addresses the issue of process change from a certain time. In fact, if we look at change points for purely time series data ... Full text Cite

Modelling species diversity through species level hierarchical modelling

Journal Article Journal of the Royal Statistical Society. Series C: Applied Statistics · February 8, 2005 Understanding spatial patterns of species diversity and the distributions of individual species is a consuming problem in biogeography and conservation. The Cape floristic region of South Africa is a global hot spot of diversity and endemism, and the Prote ... Full text Cite

Explaining Species Distribution Patterns Through Hierarchical Modeling

Journal Article Bayesian Analysis · 2005 Cite

Explaining Species diversity Through species Level Hierarchical Modeling.

Journal Article Applied Statistics · 2005 Cite

Spatial Process Modelling for Univariate and Multivariate Dynamic spatial Data

Journal Article Environmetrics · 2005 Cite

Slice sampling for simulation based fitting of spatial data models

Journal Article Statistics and Computing · January 1, 2005 An auxiliary variable method based on a slice sampler is shown to provide an attractive simulation-based model fitting strategy for fitting Bayesian models under proper priors. Though broadly applicable, we illustrate in the context of fitting spatial mode ... Full text Cite

Apartment Rent Predictions Using Spatial Modeling

Journal Article Journal of Real Estate Research · 2005 Cite

Relating Tropical Deforestation and Population Pressure through spatially Explicit Misaligned Bivariate Regression Models

Journal Article Ecological Modelling · 2005 Cite

Covariate-adjusted Spatial CDF's for Air Pollutant Data

Journal Article Journal of Agricultural, biological and environmental Statistics · 2005 Cite

Apartment rent prediction using spatial modeling

Journal Article Journal of Real Estate Research · January 1, 2005 This paper provides a new model to explain local variation in apartment rents by introducing the notion of a spatial process. This model differs from those in the literature by explicitly specifying spatial association between pairs of locations as a funct ... Cite

Spatial Modeling of House Prices Using Normalized Distance-Weighted Sums of Stationary Processes

Journal Article Journal of Business and Economic Statistics · April 1, 2004 Hedonic models are used almost universally for modeling house prices. Recognizing the importance of location, the past decade has seen increasing effort to introduce spatial considerations into such modeling. When spatial process models are used to capture ... Full text Cite

The Dynamics of Location in Home Price

Journal Article Journal of Real estate and Financial Economics · 2004 Cite

Nonstationary Spatial Modeling through Normalized Distance-Weighted Sums of Stationary Processes

Journal Article Journal of Business and Economic Statistics · 2004 Cite

Quantifying threats to biodiversity from invasive alien plants and other factors: A case study from the Cape Floristic Region

Journal Article South African Journal of Science · January 1, 2004 Nearly a third of the area of South Africa's Cape Fioristic Region has been transformed by human land use and invasive alien plants. The vulnerability of remaining natural areas to transformation has been assessed, but less attention has been given to char ... Cite

Discussion to: Statistical Research: Some Advice for Beginners

Journal Article The American Statistician · 2004 Cite

Nonstationary Multivariate Process Modelling through Spatially Varying Coregionalization (with discussion)

Journal Article Test · 2004 Cite

Nonstationary multivariate process modeling through spatially varying coregionalization

Journal Article Test · January 1, 2004 Models for the analysis of multivariate spatial data are receiving increased attention these days. In many applications it will be preferable to work with multivariate spatial processes to specify such models. A critical specification in providing these mo ... Full text Cite

Discussion of “statistical research: Some advice for beginners” by M. Hamada and R. Sitter

Journal Article American Statistician · January 1, 2004 Full text Cite

A Bayesian coregionalization approach for multivariate pollutant data

Journal Article Journal of Geophysical Research: Atmospheres · December 27, 2003 Spatial data collection increasingly turns to vector valued measurements at spatial locations. An example is the observation of pollutant measurements. Typically, several different pollutants are observed at the same sampled location, referred to as a moni ... Full text Cite

Directional Rates of Change under Spatial Process Models

Journal Article Journal of the American Statistical Association · December 1, 2003 Spatial process models are now widely used for inference in many areas of application. In such contexts interest is often in the rate of change of a spatial surface at a given location in a given direction. Examples include temperature or rainfall gradient ... Full text Cite

Hierarchical regression with misaligned spatial data: Relating ambient ozone and pediatric asthma ER visits in Atlanta

Journal Article Environmetrics · August 1, 2003 Recent work by the authors enabled a hierarchical modeling solution to the general change of support problem (COSP), where they seek to make inferences about the values of a variable at either points or regions different from those at which it has been obs ... Full text Cite

Spatial modeling and prediction under stationary non-geometric range anistropy

Journal Article Environmental and Ecological Statistics · June 1, 2003 For modeling spatial processes, we propose a rich parametric class of stationary range anisotropic covariance structures that, when applied in R2, greatly increases the scope of variogram contors. Geometric anisotropy, which provides the most common genera ... Full text Cite

Exact moment calculations for genetic models with migration, mutation, and drift.

Journal Article Theoretical population biology · May 2003 Using properties of moment stationarity we develop exact expressions for the mean and covariance of allele frequencies at a single locus for a set of populations subject to drift, mutation, and migration. Some general results can be obtained even for arbit ... Full text Cite

On the calibration of Bayesian model choice criteria

Journal Article Journal of Statistical Planning and Inference · February 1, 2003 Model choice is a fundamental problem in data analysis. With interest in hierarchical models which typically arise as Bayesian specifications, we confine ourselves to Bayesian model choice criteria. If Y denotes the observed data and T(Y) is the criterion, ... Full text Cite

Proper multivariate conditional autoregressive models for spatial data analysis.

Journal Article Biostatistics (Oxford, England) · January 2003 In the past decade conditional autoregressive modelling specifications have found considerable application for the analysis of spatial data. Nearly all of this work is done in the univariate case and employs an improper specification. Our contribution here ... Full text Cite

Spatial Modeling and Prediction Under Range Anisotropy

Journal Article Environmental and Ecological Statistics · 2003 Cite

Spatial modelling of gene frequencies in the presence of undetectable alleles

Journal Article Journal of Applied Statistics · January 1, 2003 Bayesian hierarchical models are developed to estimate the frequencies of the alleles at the HLA-C locus in the presence of non-identifiable alleles and possible spatial correlations in a large but sparse, spatially defined database from Papua New Guinea. ... Full text Cite

A Bayesian Coregionalization Approach for Multivariate Pollutant Data

Journal Article Journal of Geophysical Research · 2003 Cite

On smoothness properties of spatial processes

Journal Article Journal of Multivariate Analysis · January 1, 2003 For inferential analysis of spatial data, probability modelling in the form of a spatial stochastic process is often adopted. In the univariate case, a realization of the process is a surface over the region of interest. The specification of the process ha ... Full text Cite

Exact Moment Calculations for Genetic Models

Journal Article Journal of Theoretical Population Biology · 2003 Cite

Spatial Modeling with spatially varying Coefficient Processes

Journal Article Journal of the American Statistical Association · 2003 Cite

Bayesian Semiparametric Regression for Median Residual Life

Journal Article Scandinavian Journal of Statistics · January 1, 2003 With survival data there is often interest not only in the survival time distribution but also in the residual survival time distribution. In fact, regression models to explain residual survival time might be desired. Building upon recent work of Koftas & ... Full text Cite

Inequalities between expected marginal log-likelihoods, with implications for likelihood-based model complexity and comparison measures

Journal Article Canadian Journal of Statistics · January 1, 2003 A multi-level model allows the possibility of marginalization across levels in different ways, yielding more than one possible marginal likelihood. Since log-likelihoods are often used in classical model comparison, the question to ask is which likelihood ... Full text Cite

Zero-inflated models with application to spatial count data

Journal Article Environmental and Ecological Statistics · December 1, 2002 Count data arises in many contexts. Here our concern is with spatial count data which exhibit an excessive number of zeros. Using the class of zero-inflated count models provides a flexible way to address this problem. Available covariate information sugge ... Full text Cite

Investigating tropical deforestation using two-stage spatially misaligned regression models

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · September 1, 2002 Deforestation in the tropics has been a major concern in conservation science for more than two decades. A standard explanation is population pressure, argued through descriptive statistical summaries, but the connection between local population and forest ... Full text Cite

A nonparametric Bayesian modeling approach for cytogenetic dosimetry.

Journal Article Biometrics · September 2002 In cytogenetic dosimetry, samples of cell cultures are exposed to a range of doses of a given agent. In each sample at each dose level, some measure of cell disability is recorded. The objective is to develop models that explain cell response to dose. Such ... Full text Cite

A computational approach for full nonparametric Bayesian inference under Dirichlet process mixture models

Journal Article Journal of Computational and Graphical Statistics · August 26, 2002 Widely used parametric generalized linear models are, unfortunately, a somewhat limited class of specifications. Nonparametric aspects are often introduced to enrich this class, resulting in semiparametric models. Focusing on single or k-sample problems, m ... Full text Cite

A survey of sampling-based bayesian analysis of financial data

Journal Article International Journal of Phytoremediation · January 1, 2002 The capability of implementing a complete Bayesian analysis of experimental data has emerged over recent years due to computational advances developed within the statistical community. The objective of this paper is to provide a practical exposition of the ... Full text Cite

A simulation based approach to sample size determination under a given model and for separating models

Journal Article Statistical Science · 2002 Cite

Discussion to "Bayesian measures of model complexity and fit

Journal Article J. Royal Statistical Soc. · 2002 Cite

Prediction, interpolation and regression for spatially misaligned data points

Journal Article Sankhya A · 2002 Cite

Zero-inflated regression models for spatial count data

Journal Article Environmental and Ecological Statistics · 2002 Cite

Spatial Prediction of House Prices Using LPR and Bayesian Smoothing

Journal Article Real Estate Economics · 2002 Cite

A survey of sampling-based Bayesian analysis of financial data

Journal Article Applied Mathematical Finance · 2002 The capability of implementing a complete Bayesian analysis of experimental data has emerged over recent years due to computational advances developed within the statistical community. The objective of this paper is to provide a practical exposition of ... Cite

Modeling spatiotemporally misaligned areal and point process environmental data.

Journal Article Quantitative Methods for Current Environmental Issues · 2002 Cite

A Computational Approach for Full Nonparametric Bayesian Inference in Single and Multiple Sample Problems

Journal Article Journal of Computational and Graphical Statistics · 2002 Cite

Predicting spatial patterns of house prices using LPR and Bayesian smoothing

Journal Article Real Estate Economics · January 1, 2002 This article is motivated by the limited ability of standard hedonic price equations to deal with spatial variation in house prices. Spatial patterns of house prices can be viewed as the sum of many causal factors: Access to the central business district i ... Full text Cite

Discussion on the paper by Spiegelhalter, Best, Carlin and van der Linde

Journal Article Journal of the Royal Statistical Society. Series B: Statistical Methodology · January 1, 2002 Cite

Bayesian semiparametric median regression modeling

Journal Article Journal of the American Statistical Association · December 1, 2001 Median regression models become an attractive alternative to mean regression models when employing flexible families of distributions for the errors. Classical approaches are typically algorithmic with desirable properties emerging asymptotically. However, ... Full text Cite

Nonparametric Bayesian modeling for stochastic order

Journal Article Annals of the Institute of Statistical Mathematics · December 1, 2001 In comparing two populations, sometimes a model incorporating stochastic order is desired. Customarily, such modeling is done parametrically. The objective of this paper is to formulate nonparametric (possibly semiparametric) stochastic order specification ... Full text Cite

On computation using Gibbs sampling for multilevel models

Journal Article Statistica Sinica · October 1, 2001 Multilevel models incorporating random effects at the various levels are enjoying increased popularity. An implicit problem with such models is identifiability. From a Bayesian perspective, formal identifiability is not an issue. Rather, when implementing ... Cite

Gibbs sampling

Chapter · January 1, 2001 The vignette series concludes with 22 contributions in Theory and Methods. It is, of course, impossible to cover all of theory and methods with so few articles, but we hope that a snapshot of what was, and what may be, is achieved. This is the essence of “ ... Cite

Accommodating Scale Misalignment In Spatio-Temporal Data In: Bayesian Methods with Applications to Science

Journal Article Policy and Official Statistics · 2001 Cite

Modeling Variability Order: A Semiparametric Bayesian Approach

Journal Article Methodology and Computing In Applied Probability · 2001 Cite

On the Change of Support Problem for Spatio-Temporal Data

Journal Article Biostatistics · 2001 Cite

Gibbs Sampling

Journal Article Journal of the American Statistical Association · December 1, 2000 Full text Cite

Conditional categorical response models with application to treatment of acute myocardial infarction

Journal Article Journal of the Royal Statistical Society. Series C: Applied Statistics · December 1, 2000 For a sample of 2361 patients admitted with suspected acute myocardial infarction to a set of 37 hospitals, recorded patient response variables include eligibility for treatment with aspirin, eligibility for treatment with thrombolytics, treatment with asp ... Cite

Predicting the cumulative risk of false-positive mammograms.

Journal Article Journal of the National Cancer Institute · October 2000 BackgroundThe cumulative risk of a false-positive mammogram can be substantial. We studied which variables affect the chance of a false-positive mammogram and estimated cumulative risks over nine sequential mammograms.MethodsWe used medic ... Full text Cite

Geostatistical modelling for spatial interaction data with application to postal service performance

Journal Article Journal of Statistical Planning and Inference · September 1, 2000 The geostatistical spatial modelling framework envisions a random spatial process model Y(s) over a region S which is observed at spatial locations, say, s1,s2,...,sn. In the stationary Gaussian case, a mean function and a covariance function fully specify ... Full text Cite

Fully model-based approaches for spatially misaligned data

Journal Article Journal of the American Statistical Association · September 1, 2000 We consider inference using multivariate data that are spatially misaligned; that is, involving variables (typically counts or rates) that are aggregated over differing sets of regional boundaries. Geographic information systems enable the simultaneous dis ... Full text Cite

Modelling the cumulative risk for a false-positive under repeated screening events

Journal Article Statistics in Medicine · 2000 Screening examinations are widely utilized in detecting the presence of medical disorders, for instance, screening mammograms and clinical breast examinations for detection of breast cancer. Such procedures are invaluable in enabling early treatment but pr ... Full text Cite

Comment

Journal Article Statistical Science · January 1, 2000 Cite

Conditional Categorical Response Models with Application to Treatment Compliance for and Survival of AMI Patients

Journal Article Applied Statistics · 2000 Cite

Discussion to Bayesian Backfitting

Journal Article Statistical Science · 2000 Cite

Modeling of Multinominal data with latent structure: application to geographical mapping of human gene and haplotype frequencies

Journal Article Biostatistics · 2000 Cite

Fully Model Based Approaches for Misaligned Spatial Data

Journal Article Journal American Statistical Association · 2000 Cite

Proportional Hazards Models: A Latent Risks Approach

Journal Article Applied Statistics · 2000 Cite

Proportional hazards models: A latent competing risk approach

Journal Article Journal of the Royal Statistical Society. Series C: Applied Statistics · 2000 We propose a novel semiparametric version of the widely used proportional hazards survival model. Features include an arbitrarily rich class of continuous base-line hazards, an attractive epidemiological interpretation of the hazard as a latent competing r ... Cite

Identifiability, Improper Priors, and Gibbs Sampling for Generalized Linear Models

Journal Article Journal of the American Statistical Association · March 1, 1999 Markov chain Monte Carlo algorithms are widely used in the fitting of generalized linear models (GLMs). Such model fitting is somewhat of an art form, requiring suitable trickery and tuning to obtain results in which one can have confidence. A wide range o ... Full text Cite

Gibbs Sampling, Identifiability and Improper Priors in Generalized Linear Mixed Models

Journal Article Journal American Statistical Association · 1999 Cite

Bayesian modeling and inference for geometrically anisotropic spatial data

Journal Article Mathematical Geology · January 1, 1999 A geometrically anisotropic spatial process can be viewed as being a linear transformation of an isotropic spatial process. Customary semivariogram estimation techniques often involve ed hoc selection of the linear transformation to reduce the region to is ... Full text Cite

Approaches for optimal sequential decision analysis in clinical trials.

Journal Article Biometrics · September 1998 Unlike traditional approaches, Bayesian methods enable formal combination of expert opinion and objective information into interim and final analyses of clinical trial data. However, most previous Bayesian approaches have based the stopping decision on the ... Full text Cite

Model choice: A minimum posterior predictive loss approach

Journal Article Biometrika · January 1, 1998 Model choice is a fundamental and much discussed activity in the analysis of datasets. Nonnested hierarchical models introducing random effects may not be handled by classical methods. Bayesian approaches using predictive distributions can be used though t ... Full text Cite

Spatio-temporal modeling of residential sales data

Journal Article Journal of Business and Economic Statistics · January 1, 1998 This article focuses on the location, time, and spatio-temporal components associated with suitably aggregated data to improve prediction of individual asset values. Such effects are introduced in the context of hierarchical models, which we find more natu ... Full text Cite

A Latent Risk Approach for Modeling Individual Level Data Consisting of Multiple Event Times

Journal Article Journal of Statistical Research · 1998 Cite

Analyzing real estate data problems using the Gibbs sampler

Journal Article Real Estate Economics · January 1, 1998 Real estate data are often characterized by data irregularities: missing data, censoring or truncation, measurement error, etc. Practitioners often discard missing-or censored-data cases and ignore measurement error. We argue here that an attractive remedy ... Full text Cite

Latent Waiting Time Models for Bivariate Event Times with Censoring

Journal Article Sankhya B · 1998 Cite

Modeling and Inference for Geometrically Anisotropic Spatial Data

Journal Article Mathematical Geology · 1998 Cite

Simulation Based Model Checking for Hierarchical Models

Journal Article Test · 1998 Cite

A simulation-intensive approach for checking hierarchical models

Journal Article Test · January 1, 1998 Recent computational advances have made it feasible to fit hierarchical models in a wide range of serious applications. In the process, the question of model adequacy arises. While model checking usually addresses the entire model specification, model fail ... Full text Cite

Overdispersed generalized linear models

Journal Article Journal of Statistical Planning and Inference · October 30, 1997 Generalized linear models have become a standard class of models for data analysts. However, in some applications, heterogeneity in samples is too great to be explained by the simple variance function implicit in such models. Utilizing a two parameter expo ... Full text Cite

Broken biological size relationships: A truncated semiparametric regression approach with measurement error

Journal Article Journal of the American Statistical Association · September 1, 1997 Biological size relationships (i.e., regression of one size variable on another) are typically monotone but often break down at extreme values of the variables. Here we study the way in which a plant's biomass is apportioned to reproductive and other life ... Full text Cite

Dirichlet Process Mixed Generalized Linear Models

Journal Article Journal of the American Statistical Association · June 1, 1997 Although generalized linear models (GLM's) are an attractive and widely used class of models, they are limited in the range of density shapes that they can provide. For instance, they are unimodal exponential families of densities in the response variable ... Full text Cite

Hierarchical Spatio-Temporal Mapping of Disease Rates

Journal Article Journal of the American Statistical Association · June 1, 1997 Maps of regional morbidity and mortality rates are useful tools in determining spatial patterns of disease. Combined with sociodemographic census information, they also permit assessment of environmental justice; that is, whether certain subgroups suffer d ... Full text Cite

Bayesian Variogram Modeling for an Isotropic Spatial Process

Journal Article Journal of Agricultural, Biological, and Environmental Statistics · January 1, 1997 The variogram is a basic tool in geostatistics. In the case of an assumed isotropic process, it is used to compare variability of the difference between pairs of observations as a function of their distance. Customary approaches to variogram modeling creat ... Full text Cite

Semiparametric errors-in-variables models: A Bayesian approach

Journal Article Journal of Statistical Planning and Inference · July 1, 1996 Regression models incorporating measurement error have received much attention in the recent literature. Measurement error can arise both in the explanatory variables and in the response. We introduce a fairly general model which permits both types of erro ... Full text Cite

Comment

Journal Article Journal of the American Statistical Association · June 1, 1996 Full text Cite

Discussion to Empirical methods for combining likelihoods

Journal Article J. Amer. Statist. Assoc. · 1996 Cite

Bayesian Analysis of Financial Event Study Data

Journal Article Advances in Econometrics · 1996 Cite

Issues in Bayesian Clinical Trial Design for Categorical Endpoint Models

Journal Article Proceedings of the Biometrics Section · 1996 Cite

Efficient parametrisations for normal linear mixed models

Journal Article Biometrika · September 1, 1995 SUMMARY: The generality and easy programmability of modern sampling-based methods for maximisation of likelihoods and summarisation of posterior distributions have led to a tremendous increase in the complexity and dimensionality of the statistical models ... Full text Cite

Bayesian analysis of proportional hazards models built from monotone functions.

Journal Article Biometrics · September 1995 We consider the usual proportional hazards model in the case where the baseline hazard, the covariate link, and the covariate coefficients are all unknown. Both the baseline hazard and the covariate link are monotone functions and thus are characterized us ... Full text Cite

Comment

Journal Article Statistical Science · January 1, 1995 Full text Cite

Modeling expert opinion arising as a partial probabilistic specification

Journal Article Journal of the American Statistical Association · January 1, 1995 Expert opinion is often sought with regard to unknowns in a decision-making setting. For a univariate unknown, θ, our presumption is that such opinion is elicited as a partial probabilistic specification in the form of either probability assignments regard ... Full text Cite

Discussion to Assessment and Propagation of Model Uncertainty

Journal Article J. Royal Stat. Soc. B · 1995 Cite

On Markov chain Monte Carlo acceleration

Journal Article Journal of Computational and Graphical Statistics · 1995 Cite

Modeling expert opinion: likelihoods under incomplete probabilistic specification

Journal Article J. Amer Statist. Assoc. · 1995 Cite

Bayesian analysis of semiparametric proportional hazards models

Journal Article Biometrics · 1995 Cite

Comment on Bayesian Computation and Stochastic Systems

Journal Article Statistical Science · 1995 Cite

On Nonparametric Bayesian Inference for the Distribution of a Random Sample

Journal Article Canadian Journal of Statistics · 1995 Cite

Generalized linear models with unknown link functions

Journal Article Biometrika · June 1, 1994 SUMMARY: Generalized linear models are widely used by data analysis. However, the choice of the link function is often made arbitrarily. Here we permit the data to estimate the link function by incorporating it as an unknown in the model. Since the link fu ... Full text Cite

Bayesian model choice: asymptotic and exact calculations

Journal Article Journal Royal Statistical Society B · 1994 Cite

Bayesian analysis of concurrent time series with application to regional IBM revenue data

Journal Article Journal of Forecasting · 1994 Cite

Parametric likelihood inference for record breaking problems

Journal Article Biometrika · September 1, 1993 SUMMARY: In this paper we consider the analysis of record breaking data sets, where only observations that exceed, or only those that fall below, the current extreme value are recorded. Example application areas include industrial stress testing, meteorolo ... Full text Cite

Maximum‐likelihood estimation for constrained‐ or missing‐data models

Journal Article Canadian Journal of Statistics · January 1, 1993 In statistical models involving constrained or missing data, likelihoods containing integrals emerge. In the case of both constrained and missing data, the result is a ratio of integrals, which for multivariate data may defy exact or approximate analytic e ... Full text Cite

Discussion to the papers of Smith and Roberts, Besag and Green, and Gilks et al.

Journal Article J. Royal Statistical Society B · 1993 Cite

Discussion to "Inference from Iterative Simulation using Multiple Sequences" and "Practical Markov Chain Monte Carlo"

Journal Article Statistical Science · 1993 Cite

Bayesian analysis of population models using the Gibbs sampler

Journal Article Applied Statistics · 1993 Cite

Discussion to Approximate Bayesian Inference with the Weighted Likelihood Bootstrap

Journal Article J. Royal Statistical Society B · 1993 Cite

Meximum likelihood estimation for constrained or missing data models

Journal Article Canadian Journal of Statistics · 1993 Cite

Categorical data analysis in primary care research: log-linear models.

Journal Article Family medicine · February 1992 Primary care researchers often wish to perform multiple variable analyses using variables measured at a nominal or ordinal level. This paper provides a step-by-step description of log-linear modeling, an approach uniquely well suited to explore and describ ... Cite

Comment

Journal Article Statistical Science · January 1, 1992 Full text Cite

Rejoinder

Journal Article Journal of the American Statistical Association · January 1, 1992 Full text Cite

Bayesian analysis of constrained parameter and truncated data problems using gibbs sampling

Journal Article Journal of the American Statistical Association · January 1, 1992 Constrained parameter problems arise in a wide variety of applications, including bioassay, actuarial graduation, ordinal categorical data, response surfaces, reliability development testing, and variance component models. Truncated data problems arise nat ... Full text Cite

Hierarchical Bayesian analysis of change point problems

Journal Article Applied Statistics · 1992 Cite

Data analysis in primary care research: log linear models

Journal Article Family Medicine · 1992 Cite

Inference for the maximum cell probability under multinomial sampling

Journal Article Naval Research Logistics · 1992 Cite

Bayesian statistics without tears: a sampling-resampling perspective

Journal Article American Statistician · 1992 Cite

Bayesian analysis of constrained parameter and truncated data problems

Journal Article Journal Amer. Stat. Assoc. · 1992 Cite

Hierarchical Bayes models for the progression of HIV infection using longitudinal CD4+ counts (with discussion)

Journal Article Journal Amer. Stat. Assoc. · 1992 Cite

Discussion to Constrained Monte Carlo maximum likelihood for dependent data

Journal Article Journal Royal Statistical Society B · 1992 Cite

An iterative Monte Carlo method for nonconjugate Bayesian analysis

Journal Article Statistics and Computing · December 1, 1991 The Gibbs sampler has been proposed as a general method for Bayesian calculation in Gelfand and Smith (1990). However, the predominance of experience to date resides in applications assuming conjugacy where implementation is reasonably straightforward. Thi ... Full text Cite

Efficient generation of random variates via the ratio-of-uniforms method

Journal Article Statistics and Computing · December 1, 1991 Improvements to the conventional ratio-of-uniforms method for random variate generation are proposed. A generalized radio-of-uniforms method is introduced, and it is demonstrated that relocation of the required density via the mode can greatly improve the ... Full text Cite

Nonparametric Bayesian bioassay including ordered polytomous response

Journal Article Biometrika · September 1, 1991 Summary: Previous attempts at implementing fully Bayesian nonparametric bioassay have enjoyed limited success due to computational difficulties. We show here how this problem may be generally handled using a sampling based approach to develop desired margi ... Full text Cite

Gibbs sampling for marginal posterior expectations

Journal Article Communications in Statistics - Theory and Methods · January 1, 1991 In earlier work (Gelfand and Smith, 1990 and Gelfand et al, 1990) a sampling based approach using the Gibbs sampler was offered as a means for developing marginal posterior densities for a wide range of Bayesian problems several of which were previously in ... Full text Cite

Gibbs sampling for marginal posterior expectations

Journal Article Communications in Statistics, Theory and Methods · 1991 Cite

A note on overdispersed exponential families

Journal Article Biometrika · December 1, 1990 The issue of creating overdispersion in a given one-parameter one-dimensional exponential family, by extending it to a two-parameter exponential family with the same support, is considered. An easily verifiable sufficient condition for this is derived. It ... Full text Cite

Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling

Journal Article Journal of the American Statistical Association · December 1990 Full text Cite

Sampling-Based Approaches to Calculating Marginal Densities

Journal Article Journal of the American Statistical Association · June 1990 Full text Cite

Sampling-based approaches to calculating marginal densities

Journal Article Journal of the American Statistical Association · January 1, 1990 Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo-) based approaches to the calculation of numerical estimates of marginal probability distributions. Th ... Full text Cite

Illustration of Bayesian inference in normal data models using Gibbs sampling

Journal Article Journal of the American Statistical Association · January 1, 1990 The use of the Gibbs sampler as a method for calculating Bayesian marginal posterior and predictive densities is reviewed and illustrated with a range of normal data models, including variance components, unordered and ordered means, hierarchical growth cu ... Full text Cite

Approaches for Empirical Bayes Confidence Intervals

Journal Article Journal Amer. Stat. Assoc. · 1990 Cite

A Sample Reuse Method for Accurate Parametric Empirical Bayes Confidence Intervals

Journal Article Journal Royal Stat. Soc. Ser. B · 1990 Cite

On measuring Bayesian robustness of contaminated classes of priors

Journal Article Statistics and Decisions · 1990 Cite

Estimation for Dirichlet Mixed Models

Journal Article Naval Research Logistics Quart. · 1989 Cite

Apoproaches for Empirical Bayes Confidence Intervals for a Vector of Exponential Scale Parameters

Journal Article Computing Science and Statistics Interface · 1989 Cite

Improved estimation of a patterned covariance matrix

Journal Article Journal of Multivariate Analysis · January 1, 1989 Suppose a random vector X has a multinormal distribution with covariance matrix Σ of the form Σ = Σi=1k θiMi, where Mi's form a known complete orthogonal set and θi's are the distinct unknown eigenvalues of Σ. The problem of estimation of Σ is considered u ... Full text Cite

On the estimation of a variance ratio

Journal Article Journal of Statistical Planning and Inference · January 1, 1988 The estimation of the ratio of two independent normal variances is considered under scale invariant squared error loss function, when the means are unknown. The best invariant estimator is shown to be inadmissible. Two new classes of improved estimators ar ... Full text Cite

Improved Estimation of a Disturbance Variance

Journal Article Journal of Econometrics · 1988 Cite

A new admissibility theorem with applications to estimation of survival and hazard rates and means in the scale parameter family

Journal Article Sankhya A · 1988 Cite

Improved Estimation of Variance Components in Mixed Models

Journal Article Commun. in Statistics A · 1988 Cite

Improved estimation of the disturbance variance in a linear regression model

Journal Article Journal of Econometrics · January 1, 1988 In this paper we consider estimation of the disturbance variance in a linear regression model. A new class of improved estimators is obtained by extending results dating to Stein (1964). These estimators dominate the ordinary least squares estimator under ... Full text Cite

Reconsidering Inference in Conjoint Analysis

Journal Article Proceedings of ASA Business and Economics Section · 1987 Cite

Mean Square Error Behavior for Prediction in Linear Regression

Journal Article Communications in Statistics · 1987 Cite

Estimation in Parametric Mixture Families

Journal Article Contributions to the Theory and Application of Statistics · 1987 Cite

A NEW NONMETRIC CONJOINT METHOD - SOME PRELIMINARY-RESULTS

Journal Article ADVANCES IN CONSUMER RESEARCH · 1986 Cite

On attribute importance and relative market shares in conjoint analysis

Journal Article Proceedings of the Business and Economics Statistics Section · 1984 Cite

A simple Bayesian procedure for estimation in a conjoint model

Journal Article J. of Marketing Research · 1983 Cite

Estimation in concentral distributions

Journal Article Commun. in Statist. · 1983 Cite

A behavioral summary for completely random nets

Journal Article Bulletin of Mathematical Biology · May 1, 1982 This paper characterizes the cycle structure of a completely random net. Variables such as number of cycles of a specified length, number of cycles, number of cyclic states and length of cycle are studied. A square array of indicator variables enables conv ... Full text Cite

On the character of an distance between states in a binary switching net.

Journal Article Biological cybernetics · January 1982 Behavioral examination of binary switching net models has typically concerned itself with an examination of their cyclical character. This article considers two less frequently discussed behavioral variables--the density of "1"s in net states and the (Hamm ... Full text Cite

An Estimation Problem with Poisson Processes

Journal Article Australian Journal of Statistics · January 1, 1981 For n independent Poisson processes such that the i th process has intensity function lMi(t) =δiρ(t; α) we consider estimation of p(t; α) =∫oρ:(u; α) du. Two procedures are developed, one using exact arrival times, the other using categorical arrival times ... Full text Cite

An estimation problem for Poisson processes

Journal Article Australian Journal of Statistics · 1981 Cite

A system theoretic approach to the management of complex organizations: Management by consensus and its interaction with other management strategies

Journal Article Behavioral Science · 1980 Cite

Can judges select cases of "No Precedential Value"?

Journal Article Emory Law Review · 1980 Cite

A system theoretic approach to the management of complex organizations: Management by exception, priority, and input span in a class of fixed‐structure models

Journal Article Behavioral Science · January 1, 1979 This paper makes two main points: (1) ensembles can be used in certain circumstances to represent the perspective of a manager facing a complex organization, and (2) some management strategies can be formalized as equivalence relations over control system ... Full text Cite

A model for precedential value of appellate court decisions

Journal Article Proceedings of the Social Statistics Section · 1979 Cite

A model for complex organization with applications to managerial strategy and advertising policy

Journal Article Proceedings of the Business and Economic Statistics Section · 1978 Cite

The jury list in Connecticut: Is the voter registration list truly representative?

Journal Article Connecticut Bar Journal · 1978 Cite

Rejoinder

Journal Article Journal of the American Statistical Association · January 1, 1977 Full text Cite

The distribution of cycle lengths in a class of abstract systems

Journal Article Internat. J. General Syst. · 1977 Cite

Considerations in building jury behavior models

Journal Article Jurimetrics Journal · 1977 Cite

Are 6-member juries really as good as 12-member juries?

Journal Article Trial Magazine · 1977 Cite

Toward characterizing Boolean transformations

Journal Article Proceedings of the Society for General Systems Research · 1977 Cite

Rejoinder to On the Effect of Jury Size

Journal Article J. Amer. Statist. Assoc. · 1977 Cite

The Distribution of Cycle Lengths in a Class of Abstract Systems

Journal Article International Journal of General Systems · January 1, 1977 Systems which are built up from functionally identical elements having two inputs and two internal states are subjected to random initial positions and random structural connections such that a random determination of cycle length is achieved. This artific ... Full text Cite

COMPARISON OF SEVERAL ATTRIBUTE SAMPLING PLANS.

Journal Article Naval Research Logistics · January 1, 1976 The paper examines several types of procedures for attribute sampling inspection - the widely used Military Standard 105D plans, the lesser known Double Zero plans as developed by Ellis and the Narrow Limit gaging plans of Ott and Mundel. Each of the proce ... Cite