dynesty is an open-source Python package for dynamic nested sampling that improves efficiency in Bayesian posterior and evidence estimation compared to MCMC on certain problems.
The changing landscape of astrostatistics and astroinformatics
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abstract
The history and current status of the cross-disciplinary fields of astrostatistics and astroinformatics are reviewed. Astronomers need a wide range of statistical methods for both data reduction and science analysis. With the proliferation of high-throughput telescopes, efficient large scale computational methods are also becoming essential. However, astronomers receive only weak training in these fields during their formal education. Interest in the fields is rapidly growing with conferences organized by scholarly societies, textbooks and tutorial workshops, and research studies pushing the frontiers of methodology. R, the premier language of statistical computing, can provide an important software environment for the incorporation of advanced statistical and computational methodology into the astronomical community.
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astro-ph.IM 1years
2019 1verdicts
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dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences
dynesty is an open-source Python package for dynamic nested sampling that improves efficiency in Bayesian posterior and evidence estimation compared to MCMC on certain problems.