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Etymologia: Markov Chain Monte Carlo

机译:词源:Marco Hein蒙特卡洛

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摘要

A Markov chain Monte Carlo (MCMC) simulation is a method of estimating an unknownprobability distribution for the outcome of a complex process (a posteriordistribution). Prior (capturing the concept prior to seeing any data) distributions areused to simulate sampling from variables that have known or closely approximated distributionsin the complex process. Thus, the prior distributions are known probabilitydistributions that represent uncertainty about a particular attribute of a population priorto data sampling, and the posterior distribution represents estimated uncertainty about apopulation attribute after data sampling and is conditional on the observed data.
机译:马尔可夫链蒙特卡洛(MCMC)模拟是一种估计复杂过程结果(后验分布)的未知概率分布的方法。先验(在看到任何数据之前捕获概念)分布用于模拟在复杂过程中从已知或近似分布的变量进行采样。因此,先验分布是已知的概率分布,表示在数据采样之前关于种群的特定属性的不确定性,后验分布表示在数据采样后关于人口属性的估计不确定性,并且以观察数据为条件。

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