Reetam M
Reetam M
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Conference paper
Journal article
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Date
2023
2022
2021
2017
R. Majumder
,
B.J. Reich
(2023).
A Deep Learning Synthetic Likelihood Approximation of a Non-stationary Spatial Model for Extreme Streamflow Forecasting
. Spatial Statistics.
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DOI
S.G. Xu
,
R. Majumder
,
B.J. Reich
(2022).
SPQR: An R Package for Semi-Parametric Density and Quantile Regression
. ArXiv.
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DOI
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.
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DOI
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).
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DOI
R. Majumder
,
Q. Ji
,
N.K. Neerchal
(2022).
Optimal stock portfolio selection with a multivariate hidden Markov model
. Sankhya B.
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DOI
S. Xu
,
R. Majumder
(2022).
SPQR: Semi-Parametric Quantile Regression
. R package ver. 0.1.0, CRAN.
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Code
DOI
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.
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DOI
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.
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DOI
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