prior distribution 中文意思是什麼

prior distribution 解釋
先驗分佈
  • prior : n 普賴爾〈姓氏〉。adj 1 〈用作前置定[修飾]語〉在前的；優先的。2 〈與 to 連用〉在…之前 （opp post ...
  • 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. Compared with the regular rule - based expert system, the bayesian network based es can reason on the incomplete input information using the prior probability distribution ; the topological structure of the network being used to express the qualitative knowledge and the probability distributions of the nodes in the network being used to express the uncertainty of the knowledge, which made the knowledge representation more intuitively and more clearly ; applying the principle of the bayesian chaining rule, bidirectional inference which allow infer from the cause to the effect and from the effect to the cause can be achieved

    與一般基於規則的專家系統相比，貝葉斯網專家系統利用先驗概率分佈，可以使推理在輸入數據不完備的基礎上進行；以網路的拓撲結構表達定性知識，以網路節點的概率分佈表達知識的不確定性，從而使不確定性知識的表達直觀、明確；利用貝葉斯法則的基本原理，可以實現由因到果及由果到因的雙向推理。
  2. We a1so point out that under certain regular conditions the posterior distribution is free from prior and is approkimately normal as the volume of samples increases infinitely in this essay we discuss these regular conditions using a method similar to that of w8lker ( l967 [ 2l ] ) and heyde and johnstone ( l979tl4 ] ), but the conditions have been simplified

    、 _ 2是兩個在_ 0正值連續先驗分佈，如果在相容，則幾乎必然定理1 . l如果_ n和v _ n均為的后驗分佈且是相容的，則對于任意的有界連續！函數，有卜（川松） 。
  3. In addition, for general erlang ( n ) risk model, an integro - diifcrontial equation for the probability of ultimate ruin are presented : dickson arid hipp ( 2001 ) consider the erlang ( 2 ) risk model, and introduce the expectation of the discounted penalty h ' ( u ) which determines the joint and the marginal distribution of the time to ruin ( t ), the surplus prior to ruin ( u ( t - ) } and the deficit at ruin ( | u ( t ) | )

    Dicksonandhipp （ 2001 ）同樣考慮了erlang （ 2 ）這種風險模型，並介紹了破產時的罰金折現期望w （ u ）這一概念。由罰金折現期望可得到破產時刻（ t ） ，破產前的瞬間盈餘（ u （ t ? ） ）和破產時的赤字（ u （ t ） ）的分佈和它們的聯合分佈，並給出了罰金折現期望滿足的一積分-微分方程，由此方程得到了罰金折現期望的拉普拉斯變換。
  4. ( 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。
  5. Although the san jose center has been conducting its annual winter gift - sharing activity at the park for many years, a city ordinance now forbids public distribution of goods to the homeless without prior government approval

    雖然聖荷西小中心在此公園的冬令救濟活動已行之有年，但此地的現行法令規定，必須事先取得市政府的許可，才能公開發送物資給遊民。
  6. Monte carlo is a method that approximately solves mathematic or physical problems by statistical sampling theory. when comes to bayesian classification, it firstly gets the conditional probability distribution of the unlabelled classes based on the known prior probability. then, it uses some kind of sampler to get the stochastic data that satisfy the distribution as noted just before one by one

    蒙特卡羅是一種採用統計抽樣理論近似求解數學或物理問題的方法，它在用於解決貝葉斯分類時，首先根據已知的先驗概率獲得各個類標號未知類的條件概率分佈，然後利用某種抽樣器，分別得到滿足這些條件分佈的隨機數據，最後統計這些隨機數據，就可以得到各個類標號未知類的后驗概率分佈。
  7. In the sense of mean squares, maximum likelihood estimator, best linear unbiased estimator, taest linear invariant estimator, and good linear estimator are contracted. fourth, proposed and researched the reliability analysis method under the zero - failure data and doof data. based on the part beta distribution as the prior distribution of failure probability p, = p ( t < r, }, hierarchical bayesian estimate method was discussed, obtain the reliability analysis method under the zero - failure data and the doof data

    第四，提出並研究了無失效數據類型和doof數據類型下電連接器的可靠性分析方法，提出了以不完全beta分佈為一級先驗分佈，超參數為[ 0 ， 1 ]上的均勻分佈作為失效概率先驗分佈的多層bayes方法，結合加權最小二乘法解決了產品在無失效數據和doof數據下的可靠性分析問題。
  8. Combined with the prior distribution of the model parameters and water quality observation data, joint posterior probability function which stands for the distribution characters was obtained by bayes ' theorem

    結合模型參數的先驗分佈和水質監測數據，通過貝葉斯定理計算獲得了表徵參數分佈規律的聯合后驗概率密度函數。
  9. In the second chapter, we explicate the theoretical knowledge, bayes statistic approach, which be applied in the paper, we show the definition of the prior distribution and how to select the prior information, we show the relation of prior distribution, conditional distribution and posterior distribution, we also show statistical inference approach and the key of how to use bayes statistic approach

    第二部分內容是本文應用理論知識的簡要闡述，介紹了貝葉斯統計方法的理論，分別說明了先驗信息的定義及如何獲取，后驗分佈、條件分佈和先驗分佈三者關系，統計推斷方法及貝葉斯統計方法應用的關鍵。第三部分內容是對坦克射擊學中外彈道學的修正理論作了簡要的介紹。
  10. The fusion method for prior distribution in multi - sources of prior information

    多源驗前信息下先驗分佈的融合方法
  11. It studies the determination of population distribution, information fusion of multiple sources based on evidence theory, the consistency of prior information relative to field test information and the robustness of prior distribution

    就其中的總體分佈的確定、多源驗前信息融合問題、驗前信息與現場信息的一致性問題以及驗前分佈的穩健性進行了研究。
  12. The bayesian classification and identification method based on normal - inverted wishart prior distribution

    先驗分佈的貝葉斯分類識別方法研究
  13. Furthermore, the bayesian inference theory about unrestricted and restricted var ( p ) model under the parameter ' s prior distributions is explored. the structure of minnesota conjugate prior distribution, its hyper - parameters and determination, and the bayesian theory about var ( p ) model under the special conjugate prior distribution are all analyzed in detail

    其次，探討了非限制性和限制性var （ p ）預測模型的貝葉斯推斷理論，系統地分析了著名的minnesota共軛先驗分佈的結構及其超參數的設置，以及該先驗分佈下var （ p ）模型的貝葉斯推斷。
  14. Methods according to the bayesian conjugate prior distribution principle, the estimating methods of prior parameters (, ) of the conjugate beta distribution be (, ) of the binomial distribution was given by writing the sas programs

    方法根據貝葉斯共軛先驗分佈原理，對二項分佈的共軛貝塔分佈中的、兩個先驗參數的確定方法進行分析比較，編寫sas程序確定先驗參數。
  15. Our contribution to the documents is the introduction of jones - threshold model, a new research measure, to this field the combination of traditional aggregate accruals model and prior earnings distribution approach shows the advantages of prior distribution approach while more accurate and persuasive

    比動仇、廠段等?一十l照，冀圖收「比較出真知」之效。遺憾的是，盡管本文建立的新模型在美囚卜巾公司的分
  16. Secondly, revise factor coefficient with probability distribution, which given by experienced experts. thirdly, use bayes statistic deducing method to bind together the income rate of prior distribution and sample in formation, which makes forecast stocks in shenzhen stock market as samples. work out the series of weakly income rate

    （ 2 ）對多元回歸的因子模型的各因子權重重做修正，將一些對金融市場有較透徹了解和豐富經驗的專家提供的信息引入，作出因子系數的概率分佈（並非隨意的主觀臆造） ，對模型的結果加以修正，以便提高模型的準確度。
  17. The method of using history test datum to make prior distribution and d ? s evidence fusion theory are discussed

    討論了由歷史試驗數據確定先驗分佈的方法和多源信息的d ? s證據融合方法。
  18. By using the theory of the likelihood ratio test, a method for choosing prior distributions and classes of prior distribution is given

    摘要利用似然比檢驗原理，給出了選取先驗分佈及先驗分佈族的似然比檢驗方法。
  19. Results under the condition of the conjugate prior distribution, the prior parameters computed by three methods were similar

    結果在共軛先驗分佈的條件下，先驗矩、分位數、眾數與分位數三種方法確定的先驗分佈參數結果一致。
  20. The central works of this paper are followed : the common expression forms of expert information and the method of using max entropy and optimization method to make prior distribution of expert information are presented

    本文的主要工作如下:給出了專家信息常用的表達形式，採用最大熵方法及最優化方法給出專家信息的先驗分佈。
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