markov chain monte carlo meaning in English
马尔可夫链-蒙特卡罗理论
Examples
- For the second problem , we transform it to the computation of permanent , and monte carlo method and markov chain monte carlo method are used to sample
在计算m -齐次b zout数上，我们将它的计算转换为矩阵积和式的计算，通过montecarlo方法和markovchainmontecarlo方法来进行抽样。 - Markov chain monte carlo simulation ( mcmc ) was taken to sample the posterior distribution to get the marginal posterior probability function of the parameters , and the statistical quantities such as the mathematic expectation were calculated
通过马尔科夫链蒙特卡罗模拟对后验分布进行了采样，获得了参数的后验边缘概率密度，并在此基础上获得了参数的数学期望等统计量。 - 16 zhu s c , liu x w , wu y n . exploring texture ensembles by efficient markov chain monte carlo - toward a " trichromacy " theory of texture . ieee trans . pattern analysis and machine intelligence , 2000 , 22 : 554 - 569
对后一个问题，我们设计了一个基于k均值聚类的算法，先固定初始类别数，然后对聚类结果进行合并分析，从而对简单文档图像中采用较少的视觉类别，有效地实现了自适应处理。 - At last , it can obtain the posterior probability distibution of each unlabelled classes by analysing these stochastic data . it is easy to get a stochastic sample that satisfies some special distribution through running a special markov chain , so mcmc ( markov chain monte carlo ) is the most common monte carlo bayesian method
运行一个特定的马尔可夫链可以容易地获得满足某个特定分布的随机抽样，所以马尔可夫链蒙特卡罗( mcmc )是最常用的蒙特卡罗贝叶斯分类方法。 - Markov chain monte carlo ( mcmc ) algorithms have achieved a considerable following in the statistics and econometrics literature in the last ten years . there has been considerable research on so - called generalized autoregressive conditional heteroskedastic ( garch ) models for dealing with these methods since the remarkable works of chib and greenberg ( 1994 )
Mcmc算法在近10年来越来越受到统计界与计量经济界的广泛重视，自从chib和greenberg ( 1994 )开创性地提出了对arma模型的mcmc算法后，国内外有许多学者开始对自回归条件异方差模型的mcmc算法进行了大量的研究。