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markov chain monte carlo中文是什么意思

  • 馬爾可夫鏈-蒙特卡羅理論

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  • 例句與用法
  • 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
    在計算m -齊次b zout數(shù)上,我們將它的計算轉(zhuǎn)換為矩陣積和式的計算,通過montecarlo方法和markovchainmontecarlo方法來進行抽樣。
  • 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
    通過馬爾科夫鏈蒙特卡羅模擬對后驗分布進行了采樣,獲得了參數(shù)的后驗邊緣概率密度,并在此基礎(chǔ)上獲得了參數(shù)的數(shù)學期望等統(tǒng)計量。
  • 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
    對后一個問題,我們設(shè)計了一個基于k均值聚類的算法,先固定初始類別數(shù),然后對聚類結(jié)果進行合并分析,從而對簡單文檔圖像中采用較少的視覺類別,有效地實現(xiàn)了自適應處理。
  • 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
    運行一個特定的馬爾可夫鏈可以容易地獲得滿足某個特定分布的隨機抽樣,所以馬爾可夫鏈蒙特卡羅( mcmc )是最常用的蒙特卡羅貝葉斯分類方法。
  • 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年來越來越受到統(tǒng)計界與計量經(jīng)濟界的廣泛重視,自從chib和greenberg ( 1994 )開創(chuàng)性地提出了對arma模型的mcmc算法后,國內(nèi)外有許多學者開始對自回歸條件異方差模型的mcmc算法進行了大量的研究。
  • To obtain the prior distributions of parameters by bootstrap , i proposed the integrated sampling method to generate bootstrap samples . the method simulates a markov chain to describe the state changing procedure based on the failure time sampled by monte carlo method . and the posterior distributions of parameters are obtained by markov chain monte carlo ( mcmc ) method
    為了應用自助方法確定參數(shù)驗前分布,提出了運行故障時間和狀態(tài)的綜合抽樣方法生成自助樣本,該方法基于試驗數(shù)據(jù)用蒙特卡洛方法對故障時間進行抽樣,在故障時間抽樣值的基礎(chǔ)上,模擬馬爾可夫鏈表示系統(tǒng)狀態(tài)變化過程。
  • 百科解釋
In statistics, Markov chain Monte Carlo (MCMC) methods (which include random walk Monte Carlo methods) are a class of algorithms for sampling from probability distributions based on constructing a Markov chain that has the desired distribution as its equilibrium distribution. The state of the chain after a large number of steps is then used as a sample of the desired distribution.
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