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darrenjw.wordpress.com
Yesterday there was an RSS Read Paper meeting for the paper Unbiased Markov chain Monte Carlo with couplings by Pierre Jacob, John O'Leary and Yves F. Atchadé. The paper addresses the bias in MCMC estimates due to lack of convergence to equilibrium (the "burn-in" problem), and shows how it is possible to modify MCMC algorithms... |
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667-per-cm.net
This post could also be subtitled "Residual deviance isn't the whole story." My favorite book on logistic regression is by Dr Joseph Hilbe, Logistic Regression Models, CRC Press, 2009, Chapman & Hill. It is a solidly frequentist text, but its discussion of models and rich examples make that besides the point. Except in one case.... |
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dfm.io
[AI summary] This document provides a comprehensive guide to estimating autocorrelation times in Markov Chain Monte Carlo (MCMC) simulations. It begins by explaining the importance of autocorrelation in MCMC and how it affects the effective sample size. The text then introduces several methods for estimating autocorrelation times, including the Goodman & Weare (2010) method and a newer algorithm developed by the author (DFM 2017). The document also discusses the limitations of these methods with short chains and introduces a maximum likelihood approach using the celerite library to fit an autocorrelation model. Finally, it concludes with recommendations for choosing appropriate chain lengths based on the estimated autocorrelation times. |
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blog.foletta.net
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