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twiecki.io | ||
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jakevdp.github.io
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erikbern.com
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| | | | | I made a New Year's resolution: every plot I make during 2018 will contain uncertainty estimates. Nine months in and I have learned a lot, so I put together a summary of some of the most useful methods. | |
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dfm.io
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| | | | | [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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www.karsdorp.io
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| | | I'm a researcher in Computational Humanities and Cultural Evolution at Amsterdam's [Meertens Institute](https://meertens.knaw.nl/index.php/en/), affiliated with the Royal Netherlands Academy of Arts and Sciences. I study aspects of cultural change and experiment with methods to quantify cultural diversity. A significant aspect of my recent work is understanding and accounting for biases in these quantifications. I like to use computational models from fields such as Machine Learning, Cultural Evolution, and Ecology to aid these investigations. Beyond research, I have a passion for teaching computer programming, especially within the Humanities context. Together with [Mike Kestemont](http://mikekestemont.github.io/) and [Allen Riddell](https://www.ariddell.or... | ||
