Benchmarking NUTS, Emcee, and Nested Sampling Against Exact Ground Truth
This technical analysis benchmarks three popular probabilistic programming samplers—NumPyro's NUTS, affine-invariant MCMC via Emcee, and dynesty's nested sampling—against exact ground truth models. By evaluating their performance and failure modes, the study provides data scientists with critical insights into selecting the most reliable algorithm for complex posterior distribution inference.
Source: Towards Data Science