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Cited by 301

The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.

Fixed-Width Output Analysis for Markov Chain Monte Carlo

Open access
Jones, Galin L, Haran, Murali, Caffo, Brian S, Neath, Ronald·2006·Journal of the American Statistical Association

Abstract

Markov chain Monte Carlo is a method of producing a correlated sample to estimate features of a target distribution through ergodic averages. A fundamental question is when sampling should stop; that is, at what point the ergodic averages are good estimates of the desired quantities. We consider a method that stops the simulation when the width of a confidence interval based on an ergodic average is less than a user-specified value. Hence calculating a Monte Carlo standard error is a critical step in assessing the simulation output. We consider the regenerative simulation and batch means methods of estimating the variance of the asymptotic normal distribution. We give sufficient conditions for the strong consistency of both methods and investigate their finite-sample properties in various examples.

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Metadata

Authors
Jones, G. L., Haran, M., Caffo, B. S., & Neath, R.
Venue
Journal of the American Statistical Association
Published
2006-12-01
Volume
101
Issue
476
Pages
1537-1547
ISSN
  • 0162-1459 (ISSN-L)
  • 1537-274X
OpenAlex
W1982508956
Cited by
301
References
45
FWCI
9.15
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Fixed-Width Output Analysis for Markov Chain Monte Carlo. https://app.cochat.ai/papers/10.1198/016214506000000492
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Jones, G. L., Haran, M., Caffo, B. S., & Neath, R. (2006). Fixed-Width Output Analysis for Markov Chain Monte Carlo. Journal of the American Statistical Association. https://doi.org/10.1198/016214506000000492

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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