Journal ArticleDOI
Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
TLDR
All of the methods in this work can fail to detect the sorts of convergence failure that they were designed to identify, so a combination of strategies aimed at evaluating and accelerating MCMC sampler convergence are recommended.Abstract:
A critical issue for users of Markov chain Monte Carlo (MCMC) methods in applications is how to determine when it is safe to stop sampling and use the samples to estimate characteristics of the distribution of interest. Research into methods of computing theoretical convergence bounds holds promise for the future but to date has yielded relatively little of practical use in applied work. Consequently, most MCMC users address the convergence problem by applying diagnostic tools to the output produced by running their samplers. After giving a brief overview of the area, we provide an expository review of 13 convergence diagnostics, describing the theoretical basis and practical implementation of each. We then compare their performance in two simple models and conclude that all of the methods can fail to detect the sorts of convergence failure that they were designed to identify. We thus recommend a combination of strategies aimed at evaluating and accelerating MCMC sampler convergence, including ap...read more
Citations
More filters
Journal ArticleDOI
Brief Research Report: Bayesian versus REML Estimations with Noninformative Priors in Multilevel Single-Case Data.
Eunkyeng Baek,Eunkyeng Baek,Eunkyeng Baek,Eunkyeng Baek,Eunkyeng Baek,Eunkyeng Baek,S. Natasha Beretvas,Wim Van Den Noortgate,John M. Ferron +8 more
TL;DR: The purpose of this Monte Carlo simulation study was to examine the impact of estimation method (REML versus Bayesian with noninformative priors) on the estimation of treatment effects and on the inferences about those effects (interval coverage) for autocorrelated multiple-baseline data.
Journal ArticleDOI
When the weak are mighty: A two-sided matching approach to alliance performance
TL;DR: In this paper, the authors used a two-sided matching model to estimate the effect of each side's centrality and input quality on performance of foal sharing alliances between buyers and suppliers.
Dissertation
Statistical inference and modelling for nosocomial infections and the incorporation of whole genome sequence data
TL;DR: Stochastic epidemic models are developed and used with the aim of investigating methicillin-resistant Staphylococcus aureus transmission and intervention measures in hospital wards, and new methods were developed to model MRSA transmission, using both genetic and epidemiological data.
Journal ArticleDOI
Using simulation-based inference with panel data in health economics.
TL;DR: In this article, a review of the use of simulation-based estimators for estimating econometric models for health economics is presented, using data from the British Household Panel Survey (BHPS).
Journal ArticleDOI
Time-dependent reliability analysis using Bayesian MCMC on the reduction of reservoir storage by sedimentation
TL;DR: The objective of this study is to advance the maintenance procedures, especially the assessment of future reservoir storage, using the time-dependent reliability analysis with the Bayesian approach, and to estimate the reduction of the Soyang dam reservoir storage in South Korea.
References
More filters
Journal ArticleDOI
Equation of state calculations by fast computing machines
TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
Journal ArticleDOI
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
Journal ArticleDOI
Monte Carlo Sampling Methods Using Markov Chains and Their Applications
TL;DR: A generalization of the sampling method introduced by Metropolis et al. as mentioned in this paper is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates.
Journal ArticleDOI
Inference from Iterative Simulation Using Multiple Sequences
Andrew Gelman,Donald B. Rubin +1 more
TL;DR: The focus is on applied inference for Bayesian posterior distributions in real problems, which often tend toward normal- ity after transformations and marginalization, and the results are derived as normal-theory approximations to exact Bayesian inference, conditional on the observed simulations.
Journal ArticleDOI
Robust Locally Weighted Regression and Smoothing Scatterplots
TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.