multivariate distribution 中文意思是什麼
multivariate distribution
解釋
多變量分佈- multivariate : 第四節多變量分析
- 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...
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( 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。 -
A. p. verbyla and w. n. venables ( 1988 ) extended the ordinary growth curve model into the extension of growth curve model and obtained an estimate of the unknown parameter matrix under the conditions that the matrix of observations follow multivariate normal distribution, where every design matrix has full column rank [ 7 ]
A . p . verbyla和w . n . venables （ 1988 ）將gc模型進行了推廣，得到了推廣增長曲線模型（ theextensionofgrowthcurvemodel簡稱egc模型） ，並在觀察矩陣服從正態分佈，各設計矩陣均為列滿秩的條件下，給出了參數矩陣估計值的一種演算法。 -
Lots of research results are obtained in this field, though which are always based on two assumptions : one is that process variables are subjected to multivariate normal distribution ; the other is that samples are subjected to independent and identical distribution ( iid )
在此領域雖已獲得了大量成果，但研究基本上是在過程檢測數據服從多元正態分佈和獨立同分佈的兩個假設下進行的。 -
Considering the fact that continuous process and batch process are the two important production modes in process industry, and each of them has its respective characteristic, our works are divided into two parts, those are, monitoring of continuous processes and of batch processes. the main contribution of this thesis is as follows, 1 multivariate kernel - density estimation method is used to calculate the distribution of data and assess the impact of parametric uncertainty on the monitoring performance
由於連續生產方式和間歇生產方式是流程工業中兩種重要的生產方式，它們具有各自不同的特點，因此，本文的工作分兩大部分，即連續工業過程的監控和間歇工業過程的監控，具體包括： （ 1 ）採用多變量核密度估計方法，研究了參數不確定條件下，過程數據的分佈及其對系統監控性能的影響。 -
Simplified parameter estimation of joint distribution of extreme wind speed and wave height based on multivariate extremal theory
極值風浪聯合概率模型參數估計的簡化方法 -
In this paper, zooplankton communities, their species composition and indicator species in the east china sea and the yellow sea were examined with multivariate methods. in the southern part of the yellow sea, where was known as an important spawning ground of anchovy, the seasonal variations of zooplankton were studied in details with respect to species composition, abundance, biomass and vertical distribution. furthermore zooplankton indication of the yellow sea warm current ( yswc ) in winter was discussed
本論文用數理統計方法（包括：雙向指示種分析、多維定標序列分析、判別分析和多元回歸分析）對春、秋兩季東、黃海浮遊動物群落進行了劃分、確定各群落的指示種；對南黃海浮遊動物的種類組成、分佈及其時空變化進行了研究，並與歷史資料進行了比較；並探討了黃海冷水團對某些浮遊動物的意義，以及浮遊動物對黃海暖流指示。 -
( 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。 -
Want to build multivariate salary to distribute system, mix distribution according to work namely by allocation of factor of production union rises, hold to distribution according to work to give priority to body a variety of systems that distribute means to coexist
要建立多元的工資分配體制，即把按勞分配和按生產要素分配結合起來，堅持按勞分配為主體多種分配方式並存的制度。 -
The results of process monitoring indicate that this method is more effective than the process monitoring method based on conventional blind source signal separation. 6 ) due to the complexity of process information, a process monitoring method which applies independent component analysis and principal component analysis to extract nonnormal distributed process features and normal distributed process features is presented, which avoids the assumption that process information is subjected to multivariate normal distribution
8 ）鑒于在過程中，過程信息的平穩性並不確定，提出了一種不考慮過程平穩性能的過程監控方法，模擬表明該方法比基於傳統ica的過程監控方法具有更少的誤報率和漏報率，而比基於mspc的過程監控方法具有更少的誤報率，從而說明該方法的有效性。 -
Of course, it is often effective to apply conventional multivariate statistical process control ( mspc ) to the process whose process variables are subjected ( or approximatively subjected ) to multivariate normal distribution
本文的研究正是著眼于克服這兩大假設條件，使過程監控技術能更好地適用於實際工業生產過程而進行的。 -
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 -
Characteristics and parameter estimation of the multivariate freund exponential distribution
型指數分佈的特徵及參數估計 -
The stable distributions of shenzhen stock sub - index ( szsi ) and shanghai stock composite index ( shci ) are discussed, and the portfolio problems of probability criterion and chance - constrained programming are also analyzed. the main contents and results are as follows : 1. the basic theories of univariate stable distribution and multivariate stable distributions and stable stochastic processes are introduced
本文對深圳成分指數（ szsi ）以及上海綜合指數（ shci ）的穩定分佈、概率準則投資組合問題以及機會約束投資組合問題進行了研究，主要內容及研究結果如下： 1 .介紹了一元穩定分佈以及多元穩定分佈與穩定隨機過程的基本理論。 -
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。 -
Two primary mathematical tools used in this dissertation are principal component analysis ( pca ) and blind signal analysis ( bsa ), which are both data - driven methods. pca is not only used as feature extracting method ( where process variables are subjected to multivariate normal distribution ), but also as a tool for dimension reduction ; bsa is used to extract independent features or process blind source signals from process information in information theory sense, which is more effective than pca in describing the process
主元分析方法不僅作為一種過程特徵的提取方法（在過程信息服從多元正態分佈的情況下） ，而且也作為一種過程數據降維的主要工具（在過程盲源信號提取的情況下） ；盲源信號分析是從信息論的角度，從過程信息中提取出盡可能獨立的過程特徵信號或過程原始信源信號，它具有比主元分析更好的刻畫過程運行特徵的性能。 -
We will give the asymptotic normality and consistency of mle for multivariate model with constant correlation introduced by bollerslev ( 1990 ). 3. moreover we will introduce the agarch model with non - normal distribution and have empirical study shows that the model suggested is feasible
在多維的情形下，著重研究bollerslev （ 1990 ）提出的常數相關的多維garch模型的極大似然估計（ mle ）的漸近正態性和相合性。 -
According to the relation of conditional failure rate function and multivariate lifetime distribution built, we discuss some important qualities related to conditional failure rate function and apply the depiction to some examples
由建立的條件失效率與多維壽命分佈之間關系，討論了一些與條件失效率相關的重要性質，並舉例說明這種刻畫的運用。 -
Thus, we obtain a effective and new way to depict multivariate lifetime distribution. meanwhile, at the same reason, the thesis depicts three - dim - ensional jont failure functions and extend the depiction in n - dimensio - nal joint failure rate function
同時本文還給出了三維的聯合失效率的定義，與前面同樣的道理用所定義的三類條件失效率去刻畫它，並推廣到n維的情況。 -
S - eeing that the analysis process is loaded down with trivial details an $ is difficulty extended in multivariate case. however, taking advantage of relation between multivariate failure rate and distribution density function built by the author and endowing conditional failure rates with reasonable value joint with the fatal shock meaning, we easily obtain three - dimensional and even n - dimensional exponential distribution
鑒于該方法分析過程繁瑣，難于得到高維情形。本文另闢蹊徑，利用建立的條件失效率與多維壽命分佈之間關系，並結合致命沖擊含義賦予條件失效率合理的值，得到三維乃至一般的n維指數分佈。
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