multivariate t distribution 中文意思是什麼

multivariate t distribution 解釋
多元
  • multivariate : 第四節多變量分析
  • t : 中世紀羅馬數字的160。
  • distribution : n 1 分配，分發，配給；分配裝置[系統]；配給品；配給量；【經濟學】配給方法，配給過程；分紅；【法律...
  1. ( 1 ) the posterior distribution of the coefficient matrix, the precision matrix and covariance matrix, and their bayesian estimation under the matrix normal - wishart conjugate prior distribution. ( 2 ) the deduction of the predictive distribution, proved to be matrix t distribution. ( 3 ) the designs of bayesian multivariate mean value control charts in terms of the relationship between the multivariate wishart distribution and x2 distribution, the bayesian process capability index and its confidence lower limi

    通過多方程模型系統的統計結構，證明了矩陣正態? wishart先驗分佈是模型參數（ ， ）的共軛先驗分佈，研究了該先驗分佈下模型系數矩陣、精度陣和協方差陣的后驗分佈及其貝葉斯估計，對模型預報密度函數進行了嚴格的數學推導，並將其應用於多元質量控制領域，構造了貝葉斯均值向量聯合控制圖；結合wishart分佈與x ~ 2分佈之間的關系，設計與推斷了貝葉斯多指標過程能力指數及其貝葉斯置信下限。
  2. ( 3 ) how to design the bayesian test method about the parameter ' s linear hypothesis according to the relationship between the multivariate t distribution and f distribution. ( 4 ) the bayesian diagnosis and unit root test method about the random error series. ( 5 ) the bayesian mean value quality control chart when the variance is known and the mean value - standard error control chart when the variance is unknown

    然後，研究了擴散先驗分佈下單方程模型參數的貝葉斯估計理論，證明了模型系數的后驗分佈為多元t分佈，模型誤差項方差的后驗估計為逆gamma分佈；根據多元t分佈和f分佈之間的關系，構造了模型系數線性假設檢驗的貝葉斯方法；根據hpd置信區間構造了隨機誤差序列自相關的貝葉斯診斷和單位根檢驗方法，並利用單方程模型的貝葉斯推斷理論研究了方差已知時的貝葉斯均值控制圖和方差未知時的貝葉斯均值?標準差控制圖。
  3. Some notes on parameter estimation in a class of linear models with an error vector having multivariate t distribution

    分佈的一類線性模型下參數估計的若干注記
  4. Moreover, pca and bsa with their application in process monitoring are simple described 2 ) due to the fact that process information is n ' t always subjected to multivariate normal distribution, a process monitoring method based on pca with support vector classifier is provided, which improves the monitoring performance

    此外，還簡要地描述了主元分析方法和盲源信號分析方法及它們在過程監控中的應用。 2 ）由於過程信息並非均服從正態分佈，提出了一種基於支持向量分類器主元分析方法的過程監控方法，模擬表明提高了過程監控的性能。
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