Nested sampling algorithm

Nested sampling is a statistical method used primarily for computing the posterior distributions in Bayesian inference, particularly in cases where the parameter space is high-dimensional and complex. It was originally introduced by John Skilling in 2004 as a way to estimate the evidence for a model, which is a crucial component in Bayesian model selection.