James P. Hobert

发表

Markov Chain Monte Carlo (MCMC)

Galin L. Jones, James P. Hobert, Galin L. Jones, 2006 .

On perfect simulation for some mixtures of distributions

Christian P. Robert, D. M. Titterington, James P. Hobert, 1999, Stat. Comput..

Geometric ergodicity of the Gibbs sampler for Bayesian quantile regression

Kshitij Khare, James P. Hobert, J. Hobert, 2012, J. Multivar. Anal..

On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors

Vivekananda Roy, James P. Hobert, J. Hobert, 2010, J. Multivar. Anal..

The Data Augmentation Algorithm: Theory and Methodology

James P. Hobert, J. Hobert, 2011 .

Fast Monte Carlo Markov chains for Bayesian shrinkage models with random effects

James P. Hobert, Tavis Abrahamsen, 2019, J. Multivar. Anal..

Markov Chain Monte Carlo

James P. Hobert, Galin L. Jones, 2019 .

Trace-class Monte Carlo Markov chains for Bayesian multivariate linear regression with non-Gaussian errors

James P. Hobert, Qian Qin, J. Hobert, 2016, J. Multivar. Anal..

Comments on “Quantifying and using expert opinion for variable-selection problems in regression”

George Casella, James P. Hobert, G. Casella, 1996 .

Analysis of MCMC algorithms for Bayesian linear regression with Laplace errors

James P. Hobert, Hee Min Choi, J. Hobert, 2013, J. Multivar. Anal..

On the convergence rate of the"out-of-order"block Gibbs sampler

James P. Hobert, Zhumengmeng Jin, 2021 .

Approximating the Spectral Gap of the P\'olya-Gamma Gibbs Sampler

James P. Hobert, Bryant Davis, 2021 .

Dimension free convergence rates for Gibbs samplers for Bayesian linear mixed models

James P. Hobert, Zhumengmeng Jin, 2021 .

On the limitations of single-step drift and minorization in Markov chain convergence analysis

James P. Hobert, Qian Qin, 2021, The Annals of Applied Probability.

Convergence complexity analysis of Albert and Chib’s algorithm for Bayesian probit regression

James P. Hobert, Qian Qin, J. Hobert, 2017, The Annals of Statistics.

Crossed Random Effect Models for Multiple Outcomes in a Study of Teratogenesis

James P. Hobert, Louise Ryan, Brent A. Coull, 2001 .

A survey of Monte Carlo algorithms for maximizing the likelihood of a two-stage hierarchical model

Wolfgang Jank, James P. Hobert, James G. Booth, 2001 .

Geometric ergodicity of Gibbs samplers for Bayesian general linear mixed models with proper priors

James P. Hobert, J. Hobert, Jorge Carlos Román, 2015 .

Theoretical and methodological developments for markov chain monte carlo algorithms for bayesian regression

Vivekananda Roy, James P. Hobert, J. Hobert, 2008 .

Norm Comparisons for Data Augmentation

James P. Hobert, J. Hobert, 2007 .

When is Eaton’s Markov chain irreducible?

Ruitao Liu, James P. Hobert, Aixin Tan, 2007 .

Convergence Analysis of MCMC Algorithms for Bayesian Multivariate Linear Regression with Non‐Gaussian Errors

Kshitij Khare, James P. Hobert, Qian Qin, 2018 .

Geometric ergodicity of the Bayesian lasso

Kshitij Khare, James P. Hobert, J. Hobert, 2013 .

Analyses of Fish Species Richness with Spatial Covariate

James P. Hobert, N. Altman, J. Hobert, 1997 .

Using a Markov Chain to Construct a Tractable Approximation of an Intractable Probability Distribution

Christian P. Robert, James P. Hobert, Galin L. Jones, 2006 .

Convergence rates and asymptotic standard errors for MCMC algorithms for Bayesian probit regression

Vivekananda Roy, James P. Hobert, J. Hobert, 2007 .

Hierarchical Models: A Current Computational Perspective

James P. Hobert, J. Hobert, 2000 .

Functional Compatibility, Markov Chains and Gibbs Sampling with Improper Posteriors

George Casella, James P. Hobert, G. Casella, 1998 .

The data augmentation algorithm : Theory and methodology

James P. Hobert, J. Hobert, 2009 .

Wasserstein-based methods for convergence complexity analysis of MCMC with applications

James P. Hobert, Qian Qin, J. Hobert, 2018, The Annals of Applied Probability.

Estimation of Bayes Factors in a Class of Hierarchical Random Effects Models Using a Geometrically Ergodic MCMC Algorithm

James P. Hobert, Hani Doss, J. Hobert, 2010 .

Negative binomial loglinear mixed models

Herwig Friedl, George Casella, James P. Hobert, 2003 .

Asymptotically Stable Drift and Minorization for Markov Chains with Application to Albert and Chib's Algorithm

James P. Hobert, Qian Qin, J. Hobert, 2017 .

Spectral properties of MCMC algorithms for Bayesian linear regression with generalized hyperbolic errors

James P. Hobert, J. Hobert, Yeun Ji Jung, 2014 .