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.

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