Dootika Vats
Title
Cited by
Cited by
Year
Multivariate output analysis for Markov chain Monte Carlo
D Vats, JM Flegal, GL Jones
Biometrika 106 (2), 321-337, 2019
1512019
mcmcse: Monte Carlo Standard Errors for MCMC
JM Flegal, J Hughes, D Vats
Riverside, CA and Minneapolis, MN, 2015
117*2015
Strong consistency of multivariate spectral variance estimators in Markov chain Monte Carlo
D Vats, JM Flegal, GL Jones
Bernoulli 24 (3), 1860-1909, 2018
402018
Revisiting the gelman-rubin diagnostic
D Vats, C Knudson
arXiv preprint arXiv:1812.09384, 2018
322018
Lugsail lag windows for estimating time-average covariance matrices
D Vats, JM Flegal
arXiv preprint arXiv:1809.04541, 2018
17*2018
Geometric ergodicity of Gibbs samplers in Bayesian penalized regression models
D Vats
Electronic Journal of Statistics 11 (2), 4033-4064, 2017
132017
Batch size selection for variance estimators in MCMC
Y Liu, D Vats, JM Flegal
Methodology and Computing in Applied Probability, 1-29, 2021
8*2021
Assessing and Visualizing Simultaneous Simulation Error
N Robertson, JM Flegal, D Vats, GL Jones
Journal of Computational and Graphical Statistics, 2020
8*2020
Analyzing Markov chain Monte Carlo output
D Vats, N Robertson, JM Flegal, GL Jones
Wiley Interdisciplinary Reviews: Computational Statistics 12 (4), e1501, 2020
6*2020
Estimating Monte Carlo variance from multiple Markov chains
K Gupta, D Vats
arXiv preprint arXiv:2007.04229, 2020
32020
Efficient Bernoulli factory MCMC for intractable posteriors
D Vats, F Gonçalves, K Łatuszyński, GO Roberts
arXiv preprint arXiv:2004.07471, 2020
3*2020
stableGR: A Stable Gelman-Rubin Diagnostic for Markov Chain Monte Carlo. R package version 1.0
CP Knudson, D Vats
22019
Dimension-free Mixing for High-dimensional Bayesian Vari-able Selection
Q Zhou, J Yang, D Vats, GO Roberts, JS Rosenthal
arXiv preprint arXiv:2105.05719, 2021
12021
Output Analysis for Markov Chain Monte Carlo
D Vats
university of minnesota, 2017
12017
Monte Carlo Simulation: Are We There Yet?
D Vats, JM Flegal, GL Jones
Wiley StatsRef: Statistics Reference Online, 1-15, 2014
12014
A principled stopping rule for importance sampling
M Agarwal, D Vats, V Elvira
arXiv preprint arXiv:2108.13289, 2021
2021
Optimal Scaling of MCMC Beyond Metropolis
S Agrawal, D Vats, K Łatuszyński, GO Roberts
arXiv preprint arXiv:2104.02020, 2021
2021
Variational Rejection Particle Filtering
R Sharma, S Banerjee, D Vats, P Rai
arXiv preprint arXiv:2103.15343, 2021
2021
Bayesian equation selection on sparse data for discovery of stochastic dynamical systems
K Gupta, D Vats, S Chatterjee
arXiv preprint arXiv:2101.04437, 2021
2021
Globally-centered autocovariances in MCMC
M Agarwal, D Vats
arXiv preprint arXiv:2009.01799, 2020
2020
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Articles 1–20