Bayesian Analysis

• 

  Publication Venue For

  • Bayesian Causal Inference with Bipartite Record Linkage.  17. 2022
  • Bayesian Non-Parametric Factor Analysis for Longitudinal Spatial Surfaces.  17. 2022
  • Adaptive Variable Selection for Sequential Prediction in Multivariate Dynamic Models.  16. 2021
  • Centered Partition Processes: Informative Priors for Clustering (with Discussion)..  16:301-370. 2021
  • Comparison of Bayesian and Frequentist Multiplicity Correction for Testing Mutually Exclusive Hypotheses Under Data Dependence.  16:111-128. 2020
  • Recycling Intermediate Steps to Improve Hamiltonian Monte Carlo.  15:1087-1108. 2020
  • Restricted Type II Maximum Likelihood Priors on Regression Coefficients.  15:1281-1297. 2020
  • Latent Nested Nonparametric Priors (with Discussion)..  14:1303-1356. 2019
  • Latent nested nonparametric priors (with discussion).  14:1303-1356. 2019
  • Bayesian analysis of dynamic linear topic models.  14:53-80. 2019
  • Bayesian emulation for multi-step optimization in decision problems.  14:137-160. 2019
  • Extrinsic Gaussian processes for regression and classification on manifolds.  14:887-906. 2019
  • Mixture modeling on related samples by ψ-stick breaking and kernel perturbation.  14:161-180. 2019
  • Using Stacking to Average Bayesian Predictive Distributions (with Discussion).  13. 2018
  • Variational Hamiltonian Monte Carlo via Score Matching.  13. 2018
  • Bayesian inference and testing of group differences in brain networks.  13:29-58. 2018
  • Dirichlet process mixture models for modeling and generating synthetic versions of nested categorical data.  13:183-200. 2018
  • Supplementary Material For “Bayesian Inference And Testing Of Group Differences In Brain Networks”.  13:1-2. 2018
  • Bayesian functional data modeling for heterogeneous volatility.  12:335-350. 2017
  • Bayesian inference and model assessment for spatial point patterns using posterior predictive samples.  12:1-30. 2017
  • Bayesian mixture models with focused clustering for mixed ordinal and nominal data.  12:679-703. 2017
  • Joint species distribution modeling: Dimension reduction using Dirichlet processes.  12:939-967. 2017
  • Adaptive Shrinkage in Pólya Tree Type Models.  12. 2016
  • Incorporating marginal prior information in latent class models.  11:499-518. 2016
  • Overall objective priors.  10:189-221. 2015
  • Entity resolution with empirically motivated priors.  10:849-875. 2015
  • Bayesian regularization via graph Laplacian.  9:449-474. 2014
  • Multiple-Shrinkage Multinomial Probit Models with Applications to Simulating Geographies in Public Use Data..  8. 2013
  • Spatio-temporal modeling of legislation and votes.  8:233-268. 2013
  • Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process..  7:813-840. 2012
  • Rejoinder.  7:273-276. 2012
  • Spatial Quantile Multiple Regression Using the Asymmetric Laplace Process.  7. 2012
  • Simultaneous linear quantile regression: A semiparametric bayesian approach.  7:51-72. 2012
  • Impact of beliefs about atlantic tropical cyclone detection on conclusions about trends in tropical cyclone numbers.  6:547-572. 2011
  • Nonparametric Bayesian models through probit stick-breaking processes..  6. 2011
  • Analyzing spatial point patterns subject to measurement error.  5:97-122. 2010
  • Bayesian density regression with logistic Gaussian process and subspace projection.  5:319-344. 2010
  • Rejoinder.  5:461-464. 2010
  • Selection Sampling from Large Data Sets for Targeted Inference in Mixture Modeling..  5:1-22. 2010
  • Selection sampling from large data sets for targeted inference in mixture modeling.  5:429-450. 2010
  • A dynamic modelling strategy for bayesian computer model emulation.  4:393-412. 2009
  • Comment on article by Craigmile et al..  4:41-44. 2009
  • Inference in incidence, infection, and impact: Co-infection of multiple hosts by multiple pathogens.  4:337-366. 2009
  • Modeling space-time data using stochastic differential equations.  4:733-758. 2009
  • Modularization in Bayesian analysis, with emphasis on analysis of computer models.  4:119-150. 2009
  • Spatial Mixture Modelling for Unobserved Point Processes: Examples in Immunofluorescence Histology..  4:297-316. 2009
  • Dynamic matrix-variate graphical models.  2:69-98. 2007
  • Explaining species distribution patterns through hierarchical modeling.  1:41-92. 2006
  • Multi-scale and hidden resolution time series models.  1:947-968. 2006
  • Rejoinder.  1:103-104. 2006
  • Rejoinder.  1:457-464. 2006
  • The case for objective Bayesian analysis.  1:385-402. 2006
  • GPU-accelerated Bayesian learning in simultaneous graphical dynamic linear models 2016
  • Sequential monte carlo with adaptive weights for approximate bayesian computation 2015