Scholars@Duke
Peter David Hoff

Peter David Hoff

Professor of Statistical Science
Statistical Science
peter.hoff@duke.edu
214 Old Chemistry Bldg, Durham, NC 27708-0251

Selected Publications

Linear Source Apportionment Using Generalized Least Squares

Journal Article Technometrics · January 1, 2025 Motivated by applications to water quality monitoring using fluorescence spectroscopy, we develop the source apportionment model for high dimensional profiles of dissolved organic matter (DOM). We describe simple methods to estimate the parameters of a lin ... Full text Cite

OPTIMAL CONFORMAL PREDICTION FOR SMALL AREAS

Journal Article Journal of Survey Statistics and Methodology · November 1, 2024 Existing methods for small-area data involve a trade-off between maintaining area-level frequentist coverage rates and improving precision via the incorporation of indirect information. In this article, we develop an area-level prediction region procedure ... Full text Cite

A flexible and interpretable spatial covariance model for data on graphs

Journal Article Environmetrics · November 1, 2024 Spatial models for areal data are often constructed such that all pairs of adjacent regions are assumed to have near-identical spatial autocorrelation. In practice, data can exhibit dependence structures more complicated than can be represented under this ... Full text Cite

A LATENT VARIABLE APPROACH FOR MODELING RELATIONAL DATA WITH MULTIPLE RECEIVERS

Journal Article Annals of Applied Statistics · September 1, 2024 Directional relational event data, such as email data, often contain unicast messages (i.e., messages of one sender toward one receiver) and multicast messages (i.e., messages of one sender toward multiple receivers). The Enron email data that is the focus ... Full text Cite

Structured Shrinkage Priors

Journal Article Journal of Computational and Graphical Statistics · January 1, 2024 In many regression settings the unknown coefficients may have some known structure, for instance they may be ordered in space or correspond to a vectorized matrix or tensor. At the same time, the unknown coefficients may be sparse, with many nearly or exac ... Full text Cite

Equivariant estimation of Fréchet means

Journal Article Biometrika · December 1, 2023 The Fréchet mean generalizes the concept of a mean to a metric space setting. In this work we consider equivariant estimation of Fréchet means for parametric models on metric spaces that are Riemannian manifolds. The geometry and symmetry of such a space a ... Full text Cite

Core shrinkage covariance estimation for matrix-variate data

Journal Article Journal of the Royal Statistical Society. Series B: Statistical Methodology · November 1, 2023 A separable covariance model can describe the among-row and among-column correlations of a random matrix and permits likelihood-based inference with a very small sample size. However, if the assumption of separability is not met, data analysis with a separ ... Full text Cite

Tests of linear hypotheses using indirect information

Journal Article Canadian Journal of Statistics · September 1, 2023 In multigroup data settings with small within-group sample sizes, standard (Formula presented.) -tests of group-specific linear hypotheses can have low power, particularly if the within-group sample sizes are not large relative to the number of explanatory ... Full text Cite

Proposer of the vote of thanks to Rohe & Zeng and contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’

Journal Article Journal of the Royal Statistical Society. Series B: Statistical Methodology · September 1, 2023 n the 1930s, Psychologists began developing Multiple-Factor Analysis to decompose multivariate data into a small number of interpretable factors without any a priori knowledge about those factors. In this form of factor analysis, the Varimax factor rotatio ... Full text Cite

Routine Estimation of Dissolved Organic Matter Sources Using Fluorescence Data and Linear Least Squares

Journal Article ACS ES and T Water · August 11, 2023 Dissolved organic matter (DOM) is an important component of the biogeochemistry and ecosystem function of streams and rivers. Unlike inorganic nitrogen nutrients, organic nitrogen (DON) nutrients can vary considerably depending on the contributions of vari ... Full text Cite

Bayes-optimal prediction with frequentist coverage control

Journal Article Bernoulli · May 1, 2023 This article illustrates how indirect or prior information can be optimally used to construct a prediction region that maintains a target frequentist coverage rate. If the indirect information is accurate, the volume of the prediction region is lower on av ... Full text Cite

Smaller p-values in genomics studies using distilled auxiliary information.

Journal Article Biostatistics (Oxford, England) · December 2022 Medical research institutions have generated massive amounts of biological data by genetically profiling hundreds of cancer cell lines. In parallel, academic biology labs have conducted genetic screens on small numbers of cancer cell lines under custom exp ... Full text Open Access Cite

THE STEIN EFFECT FOR FRÉCHET MEANS

Journal Article Annals of Statistics · December 1, 2022 The Fréchet mean is a useful description of location for a probability distribution on a metric space that is not necessarily a vector space. This article considers simultaneous estimation of multiple Fréchet means from a decision-theoretic perspective, an ... Full text Cite

Smaller p-Values via Indirect Information

Journal Article Journal of the American Statistical Association · January 1, 2022 This article develops p-values for evaluating means of normal populations that make use of indirect or prior information. A p-value of this type is based on a biased frequentist hypothesis test that has optimal average power with respect to a probability d ... Full text Cite

Existence and uniqueness of the Kronecker covariance mle

Journal Article Annals of Statistics · October 1, 2021 In matrix-valued datasets the sampled matrices often exhibit correlations among both their rows and their columns. A useful and parsimonious model of such dependence is the matrix normal model, in which the covariances among the elements of a random matrix ... Full text Cite

Monte Carlo Simulation on the Stiefel Manifold via Polar Expansion

Journal Article Journal of Computational and Graphical Statistics · January 1, 2021 Motivated by applications to Bayesian inference for statistical models with orthogonal matrix parameters, we present (Formula presented.) a general approach to Monte Carlo simulation from probability distributions on the Stiefel manifold. To bypass many of ... Full text Cite

Additive and Multiplicative Effects Network Models

Journal Article Statistical Science · January 1, 2021 Network datasets typically exhibit certain types of statistical patterns, such as within-dyad correlation, degree heterogeneity, and triadic patterns such as transitivity and clustering. The first two of these can be well represented with a social relation ... Full text Cite

The Stein Effect for Frechet Means

Preprint · September 18, 2020 Link to item Cite

Exact Adaptive Confidence Intervals for Small Areas

Journal Article Journal of Survey Statistics and Methodology · April 1, 2020 In the analysis of survey data, it is of interest to estimate and quantify uncertainty about means or totals for each of several nonoverlapping subpopulations or areas. When the sample size for a given area is small, standard confidence intervals based on ... Full text Cite

Testing Sparsity-Inducing Penalties

Journal Article Journal of Computational and Graphical Statistics · January 2, 2020 Many penalized maximum likelihood estimators correspond to posterior mode estimators under specific prior distributions. Appropriateness of a particular class of penalty functions can therefore be interpreted as the appropriateness of a prior for the param ... Full text Cite

Random orthogonal matrices and the Cayley transform

Journal Article Bernoulli · January 1, 2020 Random orthogonal matrices play an important role in probability and statistics, arising in multivariate analysis, directional statistics, and models of physical systems, among other areas. Calculations involving random orthogonal matrices are complicated ... Full text Cite

Hierarchical multidimensional scaling for the comparison of musical performance styles

Journal Article Annals of Applied Statistics · January 1, 2020 Quantification of stylistic differences between musical artists is of academic interest to the music community and is also useful for other applications, such as music information retrieval and recommendation systems. Information about stylistic difference ... Full text Cite

Shared subspace models for multi-group covariance estimation

Journal Article Journal of Machine Learning Research · October 1, 2019 We develop a model-based method for evaluating heterogeneity among several p × p covariance matrices in the large p, small n setting. This is done by assuming a spiked covariance model for each group and sharing information about the space spanned by the g ... Cite

Lasso ANOVA decompositions for matrix and tensor data

Journal Article Computational Statistics and Data Analysis · September 1, 2019 Consider the problem of estimating the entries of an unknown mean matrix or tensor given a single noisy realization. In the matrix case, this problem can be addressed by decomposing the mean matrix into a component that is additive in the rows and columns, ... Full text Cite

Adaptive sign error control

Journal Article Journal of Statistical Planning and Inference · July 1, 2019 In multiple testing scenarios, typically the sign of a parameter is inferred when its estimate exceeds some significance threshold in absolute value. Typically, the significance threshold is chosen to control the experimentwise type I error rate, family-wi ... Full text Cite

Multiplicative coevolution regression models for longitudinal networks and nodal attributes

Journal Article Social Networks · May 1, 2019 We introduce a simple and extendable coevolution model for the analysis of longitudinal network and nodal attribute data. The model features parameters that describe three phenomena: homophily, contagion and autocorrelation of the network and nodal attribu ... Full text Cite

Inferential Approaches for Network Analysis: AMEN for Latent Factor Models

Journal Article Political Analysis · April 1, 2019 We introduce a Bayesian approach to conduct inferential analyses on dyadic data while accounting for interdependencies between observations through a set of additive and multiplicative effects (AME). The AME model is built on a generalized linear modeling ... Full text Cite

JOINT MEAN AND COVARIANCE MODELING OF MULTIPLE HEALTH OUTCOME MEASURES.

Journal Article The annals of applied statistics · March 2019 Health exams determine a patient's health status by comparing the patient's measurement with a population reference range, a 95% interval derived from a homogeneous reference population. Similarly, most of the established relation among health problems are ... Full text Cite

Structured Shrinkage Priors

Preprint · February 13, 2019 Link to item Cite

Exact adaptive confidence intervals for linear regression coefficients

Journal Article Electronic Journal of Statistics · January 1, 2019 We propose an adaptive confidence interval procedure (CIP) for the coefficients in the normal linear regression model. This procedure has a frequentist coverage rate that is constant as a function of the model parameters, yet provides smaller intervals tha ... Full text Cite

Adaptive multigroup confidence intervals with constant coverage

Journal Article Biometrika · June 1, 2018 Commonly used interval procedures for multigroup data attain their nominal coverage rates across a population of groups on average, but their actual coverage rate for a given group will be above or below the nominal rate, depending on the group mean. While ... Full text Cite

Adaptive Sign Error Control

Preprint · December 30, 2017 Link to item Cite

Lasso, fractional norm and structured sparse estimation using a Hadamard product parametrization

Journal Article Computational Statistics and Data Analysis · November 1, 2017 Using a multiplicative reparametrization, it is shown that a subclass of Lq penalties with q less than or equal to one can be expressed as sums of L2 penalties. It follows that the lasso and other norm-penalized regression estimates may be obtained using a ... Full text Cite

Adaptive higher-order spectral estimators

Journal Article Electronic Journal of Statistics · January 1, 2017 Many applications involve estimation of a signal matrix from a noisy data matrix. In such cases, it has been observed that estimators that shrink or truncate the singular values of the data matrix perform well when the signal matrix has approximately low r ... Full text Cite

Limitations on detecting row covariance in the presence of column covariance

Journal Article Journal of Multivariate Analysis · December 1, 2016 Many inference techniques for multivariate data analysis assume that the rows of the data matrix are realizations of independent and identically distributed random vectors. Such an assumption will be met, for example, if the rows of the data matrix are mul ... Full text Cite

A higher-order LQ decomposition for separable covariance models

Journal Article Linear Algebra and Its Applications · September 15, 2016 We develop a higher-order generalization of the LQ decomposition and show that this decomposition plays an important role in likelihood-based estimation and testing for separable, or Kronecker structured, covariance models, such as the multilinear normal m ... Full text Cite

A new approach to analyzing coevolving longitudinal networks in international relations

Journal Article Journal of Peace Research · May 1, 2016 Previous models of international conflict have suffered two shortfalls. They tend not to embody dynamic changes, focusing rather on static slices of behavior over time across a single relational dimension. These models have also been empirically evaluated ... Full text Cite

Equivariant and scale-free tucker decomposition models

Journal Article Bayesian Analysis · January 1, 2016 Analyses of array-valued datasets often involve reduced-rank array approximations, typically obtained via least-squares or truncations of array decompositions. However, least-squares approximations tend to be noisy in highdimensional settings, and may not ... Full text Cite

MULTILINEAR TENSOR REGRESSION FOR LONGITUDINAL RELATIONAL DATA.

Journal Article The annals of applied statistics · September 2015 A fundamental aspect of relational data, such as from a social network, is the possibility of dependence among the relations. In particular, the relations between members of one pair of nodes may have an effect on the relations between members of another p ... Full text Cite

Equivariant minimax dominators of the MLE in the array normal model

Journal Article Journal of Multivariate Analysis · May 1, 2015 Inference about dependence in a multiway data array can be made using the array normal model, which corresponds to the class of multivariate normal distributions with separable covariance matrices. Maximum likelihood and Bayesian methods for inference in t ... Full text Cite

Marginally specified priors for non-parametric Bayesian estimation.

Journal Article Journal of the Royal Statistical Society. Series B, Statistical methodology · January 2015 Prior specification for non-parametric Bayesian inference involves the difficult task of quantifying prior knowledge about a parameter of high, often infinite, dimension. A statistician is unlikely to have informed opinions about all aspects of such a para ... Full text Cite

Testing for nodal dependence in relational data matrices.

Journal Article Journal of the American Statistical Association · January 2015 Relational data are often represented as a square matrix, the entries of which record the relationships between pairs of objects. Many statistical methods for the analysis of such data assume some degree of similarity or dependence between objects in terms ... Full text Cite

Testing and Modeling Dependencies Between a Network and Nodal Attributes.

Journal Article Journal of the American Statistical Association · January 2015 Network analysis is often focused on characterizing the dependencies between network relations and node-level attributes. Potential relationships are typically explored by modeling the network as a function of the nodal attributes or by modeling the attrib ... Full text Cite

HIERARCHICAL ARRAY PRIORS FOR ANOVA DECOMPOSITIONS OF CROSS-CLASSIFIED DATA.

Journal Article The annals of applied statistics · March 2014 ANOVA decompositions are a standard method for describing and estimating heterogeneity among the means of a response variable across levels of multiple categorical factors. In such a decomposition, the complete set of main effects and interaction terms can ... Full text Cite

Information bounds for Gaussian copulas.

Journal Article Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability · January 2014 Often of primary interest in the analysis of multivariate data are the copula parameters describing the dependence among the variables, rather than the univariate marginal distributions. Since the ranks of a multivariate dataset are invariant to changes in ... Full text Cite

SEPARABLE FACTOR ANALYSIS WITH APPLICATIONS TO MORTALITY DATA.

Journal Article The annals of applied statistics · January 2014 Human mortality data sets can be expressed as multiway data arrays, the dimensions of which correspond to categories by which mortality rates are reported, such as age, sex, country and year. Regression models for such data typically assume an independent ... Full text Cite

Likelihoods for fixed rank nomination networks.

Journal Article Network science (Cambridge University Press) · December 2013 Many studies that gather social network data use survey methods that lead to censored, missing, or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study pa ... Full text Cite

Likelihoods for fixed rank nomination networks

Journal Article Network Science · December 2013 Cite

Modeling of the learning process in centipede games

Journal Article Stat · December 1, 2013 According to classic game theory, individuals playing a centipede game learn about the subgame perfect Nash equilibrium via repeated play of the game. We employ statistical modeling to evaluate the evidence of such learning processes while accounting for t ... Full text Cite

Comment on article by müller and mitra

Journal Article Bayesian Analysis · June 10, 2013 Due to their great flexibility, nonparametric Bayes methods have proven to be a valuable tool for discovering complicated patterns in data. The term "nonparametric Bayes" suggests that these methods inherit model-free operating characteristics of classical ... Full text Cite

Small-sample behavior of novel phase i designs: Rejoinder

Journal Article Clinical Trials · February 1, 2013 Full text Cite

Small-sample behavior of novel phase I cancer trial designs.

Journal Article Clinical trials (London, England) · February 2013 BackgroundNovel dose-finding designs for Phase I cancer clinical trials, using estimation to assign the best estimated Maximum Tolerated Dose (MTD) at each point in the experiment, most prominently via Bayesian techniques, have been widely discuss ... Full text Cite

A covariance regression model

Journal Article Statistica Sinica · April 1, 2012 Classical regression analysis relates the expectation of a response variable to a linear combination of explanatory variables. In this article, we propose a covariance regression model that parameterizes the covariance matrix of a multivariate response vec ... Full text Cite

Fast Inference for the Latent Space Network Model Using a Case-Control Approximate Likelihood.

Journal Article Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · January 2012 Network models are widely used in social sciences and genome sciences. The latent space model proposed by (Hoff et al. 2002), and extended by (Handcock et al. 2007) to incorporate clustering, provides a visually interpretable model-based spatial representa ... Full text Cite

Dose-finding designs: the role of convergence properties.

Journal Article The international journal of biostatistics · October 2011 It is common for novel dose-finding designs to be presented without a study of their convergence properties. In this article we suggest that examination of convergence is a necessary quality check for dose-finding designs. We present a new convergence proo ... Full text Cite

Separable covariance arrays via the Tucker product, with applications to multivariate relational data

Journal Article Bayesian Analysis · June 16, 2011 Modern datasets are often in the form of matrices or arrays, potentially having correlations along each set of data indices. For example, data involving repeated measurements of several variables over time may exhibit temporal correlation as well as correl ... Full text Cite

Rejoinder

Journal Article Bayesian Analysis · June 16, 2011 I thank the editor for the opportunity to expand upon the paper, and I thank the discussants for their insightful comments. In this rejoinder I elaborate on some of the topics from the discussion: the appropriateness of separable covariance models for arra ... Full text Cite

A mixed effects model for longitudinal relational and network data, with applications to international trade and conflict

Journal Article Annals of Applied Statistics · June 1, 2011 The focus of this paper is an approach to the modeling of longitudinal social network or relational data. Such data arise from measurements on pairs of objects or actors made at regular temporal intervals, resulting in a social network for each point in ti ... Full text Cite

A covariance regression model

Preprint · February 28, 2011 Link to item Cite

Hierarchical multilinear models for multiway data

Journal Article Computational Statistics and Data Analysis · January 1, 2011 Reduced-rank decompositions provide descriptions of the variation among the elements of a matrix or array. In such decompositions, the elements of an array are expressed as products of low-dimensional latent factors. This article presents a model-based ver ... Full text Cite

Array-based comparative genomic hybridization in ulcerative colitis neoplasia: single non-dysplastic biopsies distinguish progressors from non-progressors.

Journal Article Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · December 2010 Approximately 10% of ulcerative colitis patients develop colorectal neoplasia. At present, identification of this subset is markedly limited and necessitates lifelong colonoscopic surveillance for the entire ulcerative colitis population. Better risk marke ... Full text Cite

Modeling homophily and stochastic equivalence in symmetric relational data

Conference Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference · December 1, 2009 This article discusses a latent variable model for inference and prediction of symmetric relational data. The model, based on the idea of the eigenvalue decomposition, represents the relationship between two nodes as the weighted inner-product of node-spec ... Cite

Simulation of the matrix Bingham-von Mises-Fisher distribution, with applications to multivariate and relational data

Journal Article Journal of Computational and Graphical Statistics · December 1, 2009 Orthonormal matrices play an important role in reduced-rank matrix approximations and the analysis of matrix-valued data. A matrix Bingham-von Mises-Fisher distribution is a probability distribution on the set of orthonormal matrices that includes linear a ... Full text Cite

Multiplicative latent factor models for description and prediction of social networks

Journal Article Computational and Mathematical Organization Theory · December 1, 2009 We discuss a statistical model of social network data derived from matrix representations and symmetry considerations. The model can include known predictor information in the form of a regression term, and can represent additional structure via sender-spe ... Full text Cite

A hierarchical eigenmodel for pooled covariance estimation

Journal Article Journal of the Royal Statistical Society. Series B: Statistical Methodology · November 1, 2009 Although the covariance matrices corresponding to different populations are unlikely to be exactly equal they can still exhibit a high degree of similarity. For example, some pairs of variables may be positively correlated across most groups, whereas the c ... Full text Cite

Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster Random Effects Models.

Journal Article Social networks · July 2009 Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesian estimation met ... Full text Cite

The k-in-a-row up-and-down design, revisited.

Journal Article Statistics in medicine · June 2009 The percentile-finding experimental design known variously as 'forced-choice fixed-staircase', 'geometric up-and-down' or 'k-in-a-row' (KR) was introduced by Wetherill four decades ago. To date, KR has been by far the most widely used up-and-down (U&D) des ... Full text Cite

Analyzing dependencies in geo-economics and geo-politics

Book · October 30, 2008 Using data over the period from 1950 to 2000, we estimate a model of bilateral international trade to explore the linkages between (a) alliances, (b) joint memberships in international institutions, (c) mutual cooperation and (d) conflict, (e) mutual econo ... Full text Cite

Two-sided estimation of mate preferences for similarities in age, education, and religion

Journal Article Journal of the American Statistical Association · June 1, 2008 We propose a two-sided method to simultaneously estimate men's and women's preferences for relative age, education, and religious characteristics of potential mates using cross-sectional data on married couples and single individuals, in conjunction with a ... Full text Cite

Modeling homophily and stochastic equivalence in symmetric relational data

Conference Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference · January 1, 2008 This article discusses a latent variable model for inference and prediction of symmetric relational data. The model, based on the idea of the eigenvalue decomposition, represents the relationship between two nodes as the weighted inner-product of node-spec ... Cite

Modeling homophily and stochastic equivalence in symmetric relational data

Conference Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference · January 1, 2008 This article discusses a latent variable model for inference and prediction of symmetric relational data. The model, based on the idea of the eigenvalue decomposition, represents the relationship between two nodes as the weighted inner-product of node-spec ... Cite

Randomized control trial of peer-delivered, modified directly observed therapy for HAART in Mozambique.

Journal Article Journal of acquired immune deficiency syndromes (1999) · October 2007 ObjectiveTo assess the efficacy of a peer-delivered intervention to promote short-term (6-month) and long-term (12-month) adherence to HAART in a Mozambican clinic population.DesignA 2-arm randomized controlled trial was conducted between ... Full text Cite

Model averaging and dimension selection for the singular value decomposition

Journal Article Journal of the American Statistical Association · June 1, 2007 Many multivariate data-analysis techniques for an m × n matrix Y are related to the model Y = M + E, where Y is an m × n matrix of full rank and M is an unobserved mean matrix of rank K < (m ∧ n). Typically the rank of M is estimated in a heuristic way and ... Full text Cite

Extending the rank likelihood for semiparametric copula estimation

Journal Article The Annals of Applied Statistics · June 1, 2007 Full text Cite

Modeling HIV transmission risk among Mozambicans prior to their initiating highly active antiretroviral therapy.

Journal Article AIDS care · May 2007 Understanding sexual behavior and assessing transmission risk among people living with HIV-1 is crucial for effective HIV-1 prevention. We describe sexual behavior among HIV-positive persons initiating highly active antiretroviral therapy (HAART) in Beira, ... Full text Cite

Assessing antiretroviral adherence via electronic drug monitoring and self-report: an examination of key methodological issues.

Journal Article AIDS and behavior · March 2007 We explored methodological issues related to antiretroviral adherence assessment, using 6 months of data collected in a completed intervention trial involving 136 low-income HIV-positive outpatients in the Bronx, NY. Findings suggest that operationalizing ... Full text Cite

Persistent Patterns of International Commerce

Journal Article Journal of Peace Research · 2007 The authors examine a standard gravity model of international commerce augmented to include political as well as institutional influences on bilateral trade. Using annual data from 1980-2001, they estimate regression coefficients and residual dependencies ... Full text Link to item Cite

Discussion on the paper by Handcock, Raftery and Tantrum

Journal Article JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY · 2007 Cite

Model-based subspace clustering

Journal Article Bayesian Analysis · December 1, 2006 We discuss a model-based approach to identifying clusters of objects based on subsets of attributes, so that the attributes that distinguish a cluster from the rest of the population may depend on the cluster being considered. The method is based on a Póly ... Full text Cite

Positional estimation within a latent space model for networks

Conference Methodology · January 1, 2006 Recent advances in latent space and related random effects models hold much promise for representing network data. The inherent dependency between ties in a network makes modeling data of this type difficult. In this article we consider a recently develope ... Full text Cite

Subset clustering of binary sequences, with an application to genomic abnormality data.

Journal Article Biometrics · December 2005 This article develops a model-based approach to clustering multivariate binary data, in which the attributes that distinguish a cluster from the rest of the population may depend on the cluster being considered. The clustering approach is based on a multiv ... Full text Cite

Bilinear mixed-effects models for dyadic data

Journal Article Journal of the American Statistical Association · March 1, 2005 This article discusses the use of a symmetric multiplicative interaction effect to capture certain types of third-order dependence patterns often present in social networks and other dyadic datasets. Such an effect, along with standard linear fixed and ran ... Full text Cite

Clustering objects on subsets of attributes: Discussion on the paper by Friedman and Meulman

Journal Article Journal of the Royal Statistical Society. Series B: Statistical Methodology · November 26, 2004 Cite

Tumor regionality in the mouse intestine reflects the mechanism of loss of Apc function.

Journal Article Proceedings of the National Academy of Sciences of the United States of America · June 2004 Inherited colorectal cancer syndromes in humans exhibit regional specificity for tumor formation. By using mice with germline mutations in the adenomatous polyposis coli gene (Apc) and/or DNA mismatch repair genes, we have analyzed the genetic control of t ... Full text Cite

Modeling Dependencies in International Relations Networks

Journal Article Political Analysis · 2004 Despite the desire to focus on the interconnected nature of politics and economics at the global scale, most empirical studies in the field of international relations assume not only that the major actors are sovereign, but also that their relationships ar ... Full text Link to item Cite

Clustering objects on subsets of attributes - Discussion

Journal Article JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY · 2004 Cite

Bayesian methods for partial stochastic orderings

Journal Article Biometrika · June 1, 2003 We discuss two methods of making nonparametric Bayesian inference on probability measures subject to a partial stochastic ordering. The first method involves a nonparametric prior for a measure on partially ordered latent observations, and the second invol ... Full text Cite

Nonparametric estimation of convex models via mixtures

Journal Article Annals of Statistics · February 1, 2003 We present a general approach to estimating probability measures constrained to lie in a convex set. We represent constrained measures as mixtures of simple, known extreme measures, and so the problem of estimating a constrained measure becomes one of esti ... Full text Cite

Identifying international networks: Latent spaces and imputation

Conference DYNAMIC SOCIAL NETWORK MODELING AND ANALYSIS · January 1, 2003 Link to item Cite

Random effects models for network data

Conference DYNAMIC SOCIAL NETWORK MODELING AND ANALYSIS · 2003 Cite

Latent space approaches to social network analysis

Journal Article Journal of the American Statistical Association · December 1, 2002 Network models are widely used to represent relational information among interacting units. In studies of social networks, recent emphasis has been placed on random graph models where the nodes usually represent individual social actors and the edges repre ... Full text Cite

Book Reviews

Journal Article Sociological Methods & Research · November 2001 Full text Cite

Tumorigenesis in the multiple intestinal neoplasia mouse: redundancy of negative regulators and specificity of modifiers.

Journal Article Proceedings of the National Academy of Sciences of the United States of America · March 2000 The interaction between mutations in the tumor-suppressor genes Apc and p53 was studied in congenic mouse strains to minimize the influence of polymorphic modifiers. The multiplicity and invasiveness of intestinal adenomas of Apc(Min/+) (Min) mice was enha ... Full text Cite

Constrained nonparametric maximum likelihood via mixtures

Journal Article Journal of Computational and Graphical Statistics · January 1, 2000 This article discusses a new technique for calculating maximum likelihood estimators (MLEs) of probability measures when it is assumed the measures are constrained to a compact, convex set. Measures in such sets can be represented as mixtures of simple, kn ... Full text Cite

Constrained nonparametric maximum likelihood via mixtures

Journal Article Journal of Computational and Graphical Statistics · January 1, 2000 This article discusses a new technique for calculating maximum likelihood estimators (MLEs) of probability measures when it is assumed the measures are constrained to a compact, convex set. Measures in such sets can be represented as mixtures of simple, kn ... Full text Cite

Genetic identification of multiple loci that control breast cancer susceptibility in the rat.

Journal Article Genetics · May 1998 We have used a rat model of induced mammary carcinomas in an effort to identify breast cancer susceptibility genes. Using genetic crosses between the carcinoma-resistant Copenhagen (COP) and carcinoma-sensitive Wistar-Furth rats, we have confirmed the iden ... Full text Cite