NIS (Numerical Importance Sampling)

Numerical Importance Sampling (NIS) is a statistical technique used to estimate properties of complex systems or distributions by focusing on key areas that contribute most significantly to the overall result. Instead of sampling randomly from the entire space, NIS strategically targets important regions using a carefully chosen importance function. This method assigns different weights to samples based on how representative they are, improving accuracy and efficiency. It's widely used in computational fields like physics, finance, and machine learning to make precise calculations about systems that are otherwise difficult or computationally expensive to analyze directly.