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Dootika Vats
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Cited by
Year
Multivariate output analysis for Markov chain Monte Carlo
D Vats, JM Flegal, GL Jones
Biometrika 106 (2), 321-337, 2019
3322019
mcmcse: Monte Carlo Standard Errors for MCMC
JM Flegal, J Hughes, D Vats
Riverside, CA and Minneapolis, MN, 2015
193*2015
Revisiting the Gelman–Rubin diagnostic
D Vats, C Knudson
Statistical Science 36 (4), 518-529, 2021
1872021
Strong consistency of multivariate spectral variance estimators in Markov chain Monte Carlo
D Vats, JM Flegal, GL Jones
592018
Lugsail lag windows for estimating time-average covariance matrices
D Vats, JM Flegal
Biometrika 109 (3), 735-750, 2022
40*2022
Dimension‐free mixing for high‐dimensional Bayesian variable selection
Q Zhou, J Yang, D Vats, GO Roberts, JS Rosenthal
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2022
352022
Batch size selection for variance estimators in MCMC
Y Liu, D Vats, JM Flegal
Methodology and Computing in Applied Probability, 1-29, 2021
24*2021
Assessing and Visualizing Simultaneous Simulation Error
N Robertson, JM Flegal, D Vats, GL Jones
Journal of Computational and Graphical Statistics, 2020
22*2020
Solving the Poisson equation using coupled Markov chains
R Douc, PE Jacob, A Lee, D Vats
arXiv preprint arXiv:2206.05691, 2022
172022
Geometric ergodicity of Gibbs samplers in Bayesian penalized regression models
D Vats
172017
Efficient Bernoulli factory Markov chain Monte Carlo for intractable posteriors
D Vats, FB Gonçalves, K Łatuszyński, GO Roberts
Biometrika 109 (2), 369-385, 2022
16*2022
Analyzing Markov chain Monte Carlo output
D Vats, N Robertson, JM Flegal, GL Jones
Wiley Interdisciplinary Reviews: Computational Statistics 12 (4), e1501, 2020
15*2020
Optimal scaling of MCMC beyond Metropolis
S Agrawal, D Vats, K Łatuszyński, GO Roberts
Advances in Applied Probability 55 (2), 492-509, 2023
142023
stableGR: a stable Gelman-Rubin diagnostic for Markov chain Monte Carlo
C Knudson, D Vats
R package version 1, 2020
102020
Globally centered autocovariances in MCMC
M Agarwal, D Vats
Journal of Computational and Graphical Statistics 31 (3), 629-638, 2022
92022
Estimating Monte Carlo variance from multiple Markov chains
K Gupta, D Vats
arXiv preprint arXiv:2007.04229, 2020
92020
Multivariate strong invariance principles in Markov chain Monte Carlo
A Banerjee, D Vats
Electronic Journal of Statistics 18 (1), 2450-2476, 2024
52024
A principled stopping rule for importance sampling
M Agarwal, D Vats, V Elvira
Electronic Journal of Statistics 16 (2), 5570-5590, 2022
52022
Bayesian equation selection on sparse data for discovery of stochastic dynamical systems
K Gupta, D Vats, S Chatterjee
arXiv preprint arXiv:2101.04437, 2021
42021
Monte Carlo Simulation: Are We There Yet?
D Vats, JM Flegal, GL Jones
Wiley StatsRef: Statistics Reference Online, 1-15, 2021
3*2021
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Articles 1–20