Publications

R. Majumder, B.J. Reich (2023). A Deep Learning Synthetic Likelihood Approximation of a Non-stationary Spatial Model for Extreme Streamflow Forecasting. Spatial Statistics.

S.G. Xu, R. Majumder, B.J. Reich (2022). SPQR: An R Package for Semi-Parametric Density and Quantile Regression. ArXiv.

R. Majumder, N.K. Neerchal, A. Mehta (2022). Stochastic precipitation generation for the Chesapeake Bay watershed using hidden Markov models with variational Bayes parameter estimation. ArXiv.

R. Majumder, B.J. Reich, B.A. Shaby (2022). Modeling Extremal Streamflow using Deep Learning Approximations and a Flexible Spatial Process. Annals of Applied Statistics (under revision).

R. Majumder, Q. Ji, N.K. Neerchal (2022). Optimal stock portfolio selection with a multivariate hidden Markov model. Sankhya B.

S. Xu, R. Majumder (2022). SPQR: Semi-Parametric Quantile Regression. R package ver. 0.1.0, CRAN.

M.K. Gobbert, N.K. Neerchal, R. Majumder (2021). A modified minibatch sampling method for parameter estimation in hidden Markov models using stochastic variational Bayes. Proceedings in Applied Mathematics and Mechanics.

J. X. Xie, X. Fan, C. A. Drummond, R. Majumder, Y. Xie, T. Chen, L. Liu, S. T. Haller, P. S. Brewster, L. D. Dworkin, C. J. Cooper, J. Tian (2017). MicroRNA profiling in kidney disease: Plasma versus plasma-derived exosomes. Gene.