Importance Sampling: A Review
نویسندگان
چکیده
We provide a short overview of Importance Sampling – a popular sampling tool used for Monte Carlo computing. We discuss its mathematical foundation and properties that determine its accuracy in Monte Carlo approximations. We review the fundamental developments in designing efficient IS for practical use. This includes parametric approximation with optimization based adaptation, sequential sampling with dynamic adaptation through resampling and population based approaches that make use of Markov chain sampling. keywords: Importance sampling, Monte Carlo approximation, sequential sampling, resampling, Markov chain sampling.
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