Rejection Sampling Trend 2026

Rejection sampling is a Monte Carlo technique for generating random samples from complex probability distributions. By proposing candidates from a simpler distribution and rejecting those that fail an acceptance criterion, it produces exact samples. Statisticians, machine learning engineers, and computational scientists use it for Bayesian inference, physics simulations, and probabilistic modeling when direct sampling is intractable.