I am an NSF postdoctoral fellow in the Department of Statistics at the University of Warwick. My sponsoring mentor is Prof. Gareth Roberts. I am currently developing computational methods for intractable likelihoods. I am also interested in studying computational complexity for Markov chain Monte Carlo samplers and output analysis for (Markov chain) Monte Carlo methods.
Before joining Warwick, I graduated with a PhD from the School of Statistics at the University of Minnesota working with Prof. Galin Jones. My thesis was on output analysis for Markov chain Monte Carlo. Before Minnesota, I obtained my Masters from Rutgers University and completed my undergrad from Lady Shri Ram College for Women, New Delhi, India.
Curriculum Vitae (Updated May, 2019).
In July 2019, I will be joining the Department of Mathematics and Statistics at the Indian Institute of Technology, Kanpur, India, as an Assistant Professor.
- N. Robertson, J. M. Flegal, G. L. Jones, D. Vats, New visualizations for Monte Carlo simulations. arXiv.
- Y. Liu, D. Vats, J. M. Flegal. Optimal Batch Sizes for Variance Estimators in MCMC. arXiv.
- D. Vats, C.P. Knudson. Revisiting the Gelman-Rubin Diagnostic. arXiv.
- D. Vats, J. M. Flegal. Lugsail Lag Windows and their Application to MCMC. arXiv.
- D. Vats, C. Andrieu. Multivariate Ordering of Markov Chains. Read Here .
- D. Vats, J. M. Flegal, G. L. Jones. Multivariate Output Analysis for Markov Chain Monte Carlo. Biometrika, 106:321-337. Read Here. arXiv.
- D. Vats, J. M. Flegal, G. L. Jones. (2018) Strong Consistency of Multivariate Spectral Variance Estimators in Markov Chain Monte Carlo. Bernoulli, 24:1860-1909. Read Here. arXiv.
- D. Vats. (2017) Geometric Ergodicity of Gibbs Samplers in Bayesian Penalized Regression Models. Electronic Journal of Statistics, 11 (2) 4033-4064. Read Here.
- R Package mcmcse: Monte Carlo standard errors in Markov chain Monte Carlo (with J. M. Flegal, John Hughes, and Ning Dai).
Development version: GitHub.
- R package stableGR: Implements a stable Gelman-Rubin diagnostic with informed cutoffs (with Christina Knudson).
Only available on GitHub for now.
CRAN version available by July 2019.