Monte-Carlo Integration
In mathematics, Monte Carlo integration is a technique for numerical quadrature, numerical integration using pseudorandomness, random numbers. It is a particular Monte Carlo method that numerically computes a definite integral. While other algorithms usually evaluate the integrand at a regular grid, Monte Carlo randomly chooses points at which the integrand is evaluated. This method is particularly useful for higher-dimensional integrals. There are different methods to perform a Monte Carlo integration, such as Uniform distribution (continuous), uniform sampling, stratified sampling, importance sampling, Particle filter, sequential Monte Carlo (also known as a particle filter), and mean-field particle methods. Overview In numerical integration, methods such as the trapezoidal rule use a Deterministic algorithm, deterministic approach. Monte Carlo integration, on the other hand, employs a Stochastic, non-deterministic approach: each realization provides a different outcome. In M ...
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