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Preprints

Bai, R., Boland, M. R., and Chen, Y. (2020+). Fast algorithms and theory for highdimensional Bayesian varying coefficient models. Journal of the American Statistical Association (under revision).
[Preprint] [R package]

Bai, R., Lin, L., Boland, M. R., and Chen, Y. (2020+). A robust Bayesian Copas selection model for quantifying and correcting publication bias. Under review.
[Preprint] [R package]

Bai, R. (2020+). A unified computational and theoretical framework for highdimensional Bayesian additive models. Under review.
[Preprint]

Deshpande, S. K., Bai, R., Balocchi, C., Starling, J. E., and Weiss, J. (2020+). Estimating the effects of socioeconomic position on cognitive trajectories with Bayesian treed varying coefficient models. Under review.
[Preprint] [R package]
2020

Bai, R.*, Moran, G. E.*, Antonelli, J. L.*, Chen, Y., and Boland, M. R. (2020+). Spikeandslab group lassos for grouped regression and sparse generalized additive models. Journal of the American Statistical Association (in press). (* = cofirst author)
[Paper] [Supplement] [R package]
2019

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

Bai, R. and Ghosh, M. (2019). Largescale multiple hypothesis testing with the normalbeta prime prior. Statistics, 53: 12101233.
[Paper] [Supplement] [R package]
2018

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

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]
Selected Works in Progress

Bai, R., Jeong, S., and Ročková, V. (2020+). Minimax rates and adaptive procedures for nonparametric regression in the overdispersed exponential family.

Bai, R.*, Balocchi, C.*, Liu, J., Canelón, S., George, E. I., Chen, Y., and Boland, M. R. (2020+). A Bayesian hierarchical modeling framework for geospatial analysis of adverse pregnancy outcomes. (* = cofirst author)

Bai, R., Ročková, V., and George, E. I. (2020+). Spikeandslab meets lasso: A review of the spikeandslab lasso.

^{†} Bai, R. and Qin, Q. (2020+). Analysis of MCMC algorithms for Gaussian process regression with automatic relevance determination kernels. († = alphabetical ordering)