## James P. Hobert

## Publications since 2015:

- Qin, Q. and Hobert, J. P. (2019+). Convergence complexity
analysis of Albert and Chib's algorithm for Bayesian probit
regression,
* Annals of Statistics*, to appear.

- Abrahamsen, T. and Hobert, J. P. (2019). Fast Monte Carlo Markov
chains for Bayesian shrinkage models with random effects,
*
Journal of Multivariate Analysis*, **169**: 61-80.

- Hobert, J. P., Jung, Y. J., Khare, K. and Qin,
Q. (2018). Convergence analysis of MCMC algorithms for Bayesian
multivariate linear regression with non-Gaussian errors,
*
Scandinavian Journal of Statistics*, **45**: 513-533.

- Qin, Q. and Hobert, J. P. (2018). Trace-class Monte Carlo Markov
chains for Bayesian multivariate linear regression with
non-Gaussian errors,
* Journal of Multivariate
Analysis*, **166**: 335-345.

- Pal, S., Khare, K. and Hobert, J. P. (2017). Trace class Markov
chains for Bayesian inference with generalized double Pareto
shrinkage priors,
* Scandinavian Journal of
Statistics*, **44**: 307-323.

- Abrahamsen, T. and Hobert, J. P. (2017). Convergence analysis of
block Gibbs samplers for Bayesian linear mixed models with p >
N,
*Bernoulli*, **23**: 459-478.

- Hobert, J. P. and Khare, K. (2016). Discussion of "Posterior
inference in Bayesian quantile regression with asymmetric
Laplace likelihood," by Yang, Wang and He,
* International
Statistical Review*, **84**: 349-356.

- Choi, H. M. and Hobert, J. P. (2016). A comparison theorem for
data augmentation algorithms with applications,
*Electronic
Journal of Statistics*, **10**: 308-329.

- Pal, S., Khare, K. and Hobert, J. P. (2015). Improving the DA
algorithm in the two-block setup,
*Journal of Computational
and Graphical Statistics*, **24**: 1114-1133.

- Hobert, J. P. and Khare, K. (2015). Computable upper bounds on
the distance to stationarity for Jovanovski and Madras's Gibbs
sampler,
*Annales de la Faculte des Sciences de
Toulouse*, **24**: 935-947.

- Tan, A., Doss, H. and Hobert, J. P. (2015). Honest importance
sampling with multiple Markov chains,
*Journal of
Computational and Graphical Statistics*, **24**:
792-826.

- Román, J. C. and Hobert, J. P. (2015). Geometric ergodicity
of Gibbs samplers for Bayesian general linear mixed models with
proper priors,
*Linear Algebra and its
Applications*, **473**: 54-77.