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bayesian estimation in Chinese

Pronunciation:
How to pronounce "bayesian estimation""bayesian estimation" in a sentence

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  • 貝葉斯估計(jì)

Examples

  • Bayesian estimation of time series model with trend
    時(shí)間序列趨勢項(xiàng)的貝葉斯估計(jì)
  • Bayesian estimation of variance factor in the nonlinear model
    非線形模型方差的貝葉斯估計(jì)
  • Bayesian estimation of a circle
    圓參數(shù)的貝葉斯估計(jì)
  • Implementation of measuring the difference of phase based on bayesian estimation
    基于貝葉斯頻譜估計(jì)的相位差測量及實(shí)現(xiàn)
  • Bayesian estimation for the parameter of exponential distribution under multiply type - censoring
    定數(shù)截尾數(shù)據(jù)缺失場合下雙參數(shù)指數(shù)分布參數(shù)的貝葉斯估計(jì)
  • Decision theory , statistical classification , maximum likelihood and bayesian estimation , non - parametric methods , unsupervised learning and clustering
    決策理論，統(tǒng)計(jì)分類，最大似然和貝葉斯估計(jì)，非參數(shù)方法，非監(jiān)督的學(xué)習(xí)與聚類。
  • In ps alt , we obtain the bayesian estimation of each parameter and marginal posterior density when the prior density of shape parameter is continuous using laplace method under ce model . in ssalt , we obtain the bayesian estimation of each parameter using the same method
    在序加試驗(yàn)下，對(duì)于逆冪律模型，給出了參數(shù)的bayes統(tǒng)計(jì)分析，并利用laplace方法解決了分布的形狀參數(shù)取為連續(xù)先驗(yàn)時(shí)各參數(shù)的bayes估計(jì)和參數(shù)后驗(yàn)邊際密度。
  • This paper analysed a kind of model of the general stochastic epidemic in regular population , discussed its solution and the solution ' s property , and further carried out bayesian estimation for its parameter , also gave a method of determining the super parameter of the prior distribution
    摘要介紹了一類在固定人口條件下的標(biāo)準(zhǔn)流行病的隨機(jī)模型，討論了該模型的解及其性質(zhì)，進(jìn)一步對(duì)其參數(shù)進(jìn)行了貝葉斯估計(jì)，對(duì)其先驗(yàn)分布的超參數(shù)也給出了確定的方法。
  • This paper studies 3 kinds of algorithms : the viterbi algorithm , multiresolutional algorithm based on wavelet transformation and bayesian bootstrap algorithm . the viterbi algorithm is based on the hidden markov model theory and it is a kind of map estimation , this paper studies this algorithm and puts up an algorithm that suits for filtering in the presence of interference . multiresolutional algorithm takes full advantage of multiresolutional data , we can see it has a better filtering ability than the traditional filtering methods ; bootstrap algorithm is a recursive bayesian estimation , it describes the probability density function by the samples , so it can be used to nonlinear non - gaussion filtering , the simulation result of the two groundings is presented
    Viterbi算法以隱馬爾可夫理論為基礎(chǔ)，是一種最大后驗(yàn)概率估計(jì)方法，本文對(duì)該算法進(jìn)行了研究，給出了一種適合于非高斯干擾條件下的濾波方法；多分辨分析方法充分利用到了多分辨率測量數(shù)據(jù)所包含的信息，從仿真結(jié)果中可以看出，該方法的濾波精度要高于傳統(tǒng)的濾波算法；自主濾波方法是一種遞推貝葉斯估計(jì)算法，它利用采樣點(diǎn)來描述目標(biāo)狀態(tài)的概率密度函數(shù)，因而適用于非線性、非高斯條件下的濾波，本文分別對(duì)這兩種情況下的濾波進(jìn)行了仿真。
  • ( 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(tǒng)的統(tǒng)計(jì)結(jié)構(gòu)，證明了矩陣正態(tài)? wishart先驗(yàn)分布是模型參數(shù)( ， )的共軛先驗(yàn)分布，研究了該先驗(yàn)分布下模型系數(shù)矩陣、精度陣和協(xié)方差陣的后驗(yàn)分布及其貝葉斯估計(jì)，對(duì)模型預(yù)報(bào)密度函數(shù)進(jìn)行了嚴(yán)格的數(shù)學(xué)推導(dǎo)，并將其應(yīng)用于多元質(zhì)量控制領(lǐng)域，構(gòu)造了貝葉斯均值向量聯(lián)合控制圖；結(jié)合wishart分布與x ~ 2分布之間的關(guān)系，設(shè)計(jì)與推斷了貝葉斯多指標(biāo)過程能力指數(shù)及其貝葉斯置信下限。

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