ほう
メトロポリスヘイスティングス法
1. Metropolis-Hastings algorithmComputing
2. Metropolis–Hastings algorithmIn statistics and in statistical physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. This sequence can be used to approximate the distribution (i.e. , to generate a histogram), or to compute an integral (such as an expected value).
Read “Metropolis–Hastings algorithm” on English Wikipedia
Read “メトロポリス・ヘイスティングス法” on Japanese Wikipedia
Read “Metropolis–Hastings algorithm” on DBpedia
Read “Metropolis–Hastings algorithm” on English Wikipedia
Read “メトロポリス・ヘイスティングス法” on Japanese Wikipedia
Read “Metropolis–Hastings algorithm” on DBpedia
メトロポリス・ヘイスティングス法 【メトロポリスヘイスティングスほう】
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