Papers Under Invited Revision

Bai, R., Boland, M. R., and Chen, Y. (2019+). Fast algorithms and theory for highdimensional Bayesian varying coefficient models. In revision for Journal of the American Statistical Association.
[preprint]

Bai, R.*, Moran, G. E.*, Antonelli, J. L.*, Chen, Y., and Boland, M. R. (2019+). Spikeandslab group lassos for grouped regression and sparse generalized additive models. In revision for Journal of the American Statistical Association. (* = cofirst author)
[preprint]
2019

Bai, R. and Ghosh, M. (2019). On the beta prime prior for scale parameters in highdimensional Bayesian regression models. Statistica Sinica, in press.
[pdf] [supplement]

Bai, R. and Ghosh, M. (2019). Largescale multiple hypothesis testing with the normalbeta prime prior. Statistics, in press.
[pdf] [supplement]
2018

Bai, R. and Ghosh, M. (2018). Highdimensional multivariate posterior consistency under globallocal shrinkage priors. Journal of Multivariate Analysis, 167: 157170.
[pdf] [supplement]

Duerr, I., Merrill, H. R., Wang, C., Bai, R., Boyer, M. J., Dukes, M. D., and Bliznyuk, N. (2018). Forecasting urban water demand with statistical and machine learning methods using large spacetime data. Environmental Modeling and Software, 102: 2938.
[link]
Workings Papers and Papers in Preparation

Deshpande, S. K., Bai, R., Balocchi, C., and Starling, J. E. (2019+). VCBART: Bayesian trees meet varying coefficients. In preparation.

Bai, R., Boland, M. R., and Chen, Y. (2019+). A robust Bayesian Copas selection model for detecting and correcting publication bias. In preparation.

^{†} Bai, R. and Qin, Q. (2019+). Analysis of MCMC algorithms for Gaussian process regression with automatic relevance determination kernels. In preparation. († = alphabetical ordering)

Bai, R., Ročková, V., and George, E. I. (2019+). Spikeandslab meets lasso: A review of the spikeandslab lasso. In preparation.