Julia wrapper for UltraNest: advanced nested sampling for model comparison and parameter estimation
Author bat
4 Stars
Updated Last
2 Years Ago
Started In
December 2020


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This is a Julia wrapper for Python nested sampling package UltraNest.

Nested sampling allows Bayesian inference on arbitrary user-defined likelihoods. In particular, posterior probability distributions on model parameters are constructed, and the marginal likelihood ("evidence") Z is computed. The former can be used to describe the parameter constraints of the data, the latter can be used for model comparison (via Bayes factors) as a measure of the prediction parsimony of a model.

UltraNest provides novel, advanced techniques (see how it works). They are especially remarkable for being free of tuning parameters and theoretically justified. Beyond that, UltraNest has support for Big Data sets and high-performance computing applications.

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