markov chain monte carlo 中文意思是什麼

markov chain monte carlo 解釋
馬爾可夫鏈-蒙特卡羅理論
  • markov : 馬爾科夫
  • chain : n 1 鏈子，鏈條；項圈；表鏈。2 連鎖；連續，一系列，一連串；（山）脈。3 〈常 pl 〉鐐銬；羈絆，拘束...
  • monte : n. （一種西班牙式）紙牌戲。 three-card monte （起源於墨西哥的）三張牌戲。n. 蒙提〈男子名, Montague 的昵稱〉。
  • carlo : 卡爾羅
  1. 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演算法在近10年來越來越受到統計界與計量經濟界的廣泛重視，自從chib和greenberg （ 1994 ）開創性地提出了對arma模型的mcmc演算法后，國內外有許多學者開始對自回歸條件異方差模型的mcmc演算法進行了大量的研究。
  2. 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驗前分佈，提出了運行故障時間和狀態的綜合抽樣方法生成自助樣本，該方法基於試驗數據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上，模擬馬爾可夫鏈表示系統狀態變化過程。
  3. Furthermore, monte carlo sampling method is used to simulate reservoir lithofacies, based on different neighborhood systems of markov chain models

    隨后，對不同鄰域系統的馬爾可夫鏈模型採用蒙特卡羅抽樣方法進行了儲層巖相隨機模擬試驗。
  4. 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，我們設計了一個基於k均值聚類的演算法，先固定初始類別數，然後對聚類結果進行合併分析，從而對簡單文檔圖像中採用較少的視覺類別，有效地實現了自適應處理。
  5. 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數上，我們將它的計算轉換為矩陣積和式的計算，通過montecarlo方法和markovchainmontecarlo方法來進行抽樣。
  6. 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佈進行了采樣，獲得了參數的后驗邊緣概率密度，並在此基礎上獲得了參數的數學期望等統計量。
  7. 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佈的隨機抽樣，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。
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