275 citations · 619 across the 18 of their papers we have counts for
10 papers · 1 filter
Inference Optimal Long Run Variance Estimation with Lugsail Kernels
Rebecca P. Kurtz-Garcia, James M. Flegal
For datasets with unknown but stationary serial dependence, a robust long run variance estimator is essential to handle diverse scenarios. Spectral variance estimators are commonly…
Weighted batch means estimators in Markov chain Monte Carlo
Ying Liu, James M. Flegal
This paper proposes a family of weighted batch means variance estimators, which are computationally efficient and can be conveniently applied in practice. The focus is on Markov ch…
Batch size selection for variance estimators in MCMC
Ying Liu, Dootika Vats, James M. Flegal
We consider batch size selection for a general class of multivariate batch means variance estimators, which are computationally viable for high-dimensional Markov chain Monte Carlo…
Multivariate Output Analysis for Markov chain Monte Carlo
Dootika Vats, James M. Flegal, Galin L. Jones
Markov chain Monte Carlo (MCMC) produces a correlated sample for estimating expectations with respect to a target distribution. A fundamental question is when should sampling stop…
Estimating standard errors for importance sampling estimators with multiple Markov chains
Vivekananda Roy, Aixin Tan, James M. Flegal
The naive importance sampling estimator, based on samples from a single importance density, can be numerically unstable. Instead, we consider generalized importance sampling estima…
Strong Consistency of Multivariate Spectral Variance Estimators
Dootika Vats, James M. Flegal, Galin L. Jones
Markov chain Monte Carlo (MCMC) algorithms are used to estimate features of interest of a distribution. The Monte Carlo error in estimation has an asymptotic normal distribution wh…
Relative fixed-width stopping rules for Markov chain Monte Carlo simulations
James M. Flegal, Lei Gong
Markov chain Monte Carlo (MCMC) simulations are commonly employed for estimating features of a target distribution, particularly for Bayesian inference. A fundamental challenge is…
Markov Chain Monte Carlo Estimation of Quantiles
Charles Doss, James M. Flegal, Galin L. Jones +1
We consider quantile estimation using Markov chain Monte Carlo and establish conditions under which the sampling distribution of the Monte Carlo error is approximately Normal. Furt…
Batch means and spectral variance estimators in Markov chain Monte Carlo
James M. Flegal, Galin L. Jones
Calculating a Monte Carlo standard error (MCSE) is an important step in the statistical analysis of the simulation output obtained from a Markov chain Monte Carlo experiment. An MC…
Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?
James M. Flegal, Murali Haran, Galin L. Jones
Current reporting of results based on Markov chain Monte Carlo computations could be improved. In particular, a measure of the accuracy of the resulting estimates is rarely reporte…