后验分布的英文

• posterior distribution

• "后验"英文翻译    posterior; posteriority; a p ...
• "分布"英文翻译    distribute; spread; scatter; ...
• "截尾后验分布" 英文翻译 :    truncated posterior distribution
• "最终后验分布" 英文翻译 :    final posterior distribution
• "贝叶斯后验分析" 英文翻译 :    bayesian posterior analysis
• "经验分布" 英文翻译 :    empiric distribution; empirical distribution; empitical distribution
• "实验分布" 英文翻译 :    empirical distribution; experimental distribution
• "先验分布" 英文翻译 :    a prior distribution; a priori distribution; apriori distribution; prior distribution
• "后验概率分布" 英文翻译 :    posterior probability distribution
• "经验分布函数" 英文翻译 :    empirical distribution function
• "经验分布曲线" 英文翻译 :    empirical distribution curve
• "扩散先验分布" 英文翻译 :    diffusion prior to distribution
• "先验分布序列" 英文翻译 :    sequence of prior distributions
• "后验" 英文翻译 :    posterior; posteriority; [拉丁语] a posteriori
• "不提供信息的先验分布" 英文翻译 :    noninformative prior distribution
• "经验分别分布在汽车、汽车业的销售过程" 英文翻译 :    experience in vehicle distribution respectively, sales processes in the automotive industry
• "后验的" 英文翻译 :    a posterior
• "后验方差" 英文翻译 :    posterior variance
• "后验概率" 英文翻译 :    a posterier probability; apa posteriori probability; bayes theorem; posterior probability; probability a posteriori
• "后验概念" 英文翻译 :    aposterior concept
• "后验估计" 英文翻译 :    a posteriori estimation
• "后验估算" 英文翻译 :    posterior estimate
• "后验估值" 英文翻译 :    a posteriori estimate
• "后验可能性" 英文翻译 :    posterior odds
• "后验平均值" 英文翻译 :    posterior mean

• However , for non - linear models and non - gaussian noise , such closed form expressions are almost impossible to obtain , and sequtial monte carlo method provides its approximation
  这种方法的基本思想是产生服从后验分布的样本，并对其进行加权，以得到后验密度函数的近似解。
• From a bayesian viewpoint , a growth curve model is studied . with a conjugate prior , the posterior distribution of and that of are given respectively
  摘要从贝叶斯观点利用共轭先验考查了增长曲线模型。得到了参数和协方差的边缘后验分布，并在此基础上给出的后验估计、估计域和的后验估计。
• It uses particles to describe the state space . the discretely random measure composed by particles and associated weights approximates to the true posterior state distribution , and is updated by iteration of the algorithm
  它采用粒子描述状态空间,用由粒子及其权重组成的离散随机测度近似真实的状态后验分布,并且根据算法递推更新离散随机测度。
• 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
  通过马尔科夫链蒙特卡罗模拟对后验分布进行了采样，获得了参数的后验边缘概率密度，并在此基础上获得了参数的数学期望等统计量。
• Here we developed the general arma ( p , q ) - garch ( r , s ) - m ( k ) models , which maybe become increasingly important for estimating volatility returns and exogenous shocks for finance data . after we present the posterior distribution of the model and the full conditional distributions of all the parameters of the model , we develop a hybrid metropolis - hastings algorithm for estimating the parameters of arma - garch - m models based on the works of bayesian chib and greenberg ( 1994 ) and nakatsuma ( 2000 ) . here we simplified the estimations in ma and garch block
  作为该模型的推广，我们在本文中提出了一个一般的arma ( p , q ) - garch ( r , s ) - m ( k )模型，并在详细给出模型的后验分布以及模型的所有参数的满条件分布的基础上，结合chibandgreenberg ( 1994 )与nakatsuma ( 2000 )等人的工作，对此新模型设计了一个可行的混合metropolis - hastings算法，简化了ma块与garch块的估计。
• 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是两个在_ 0正值连续先验分布，如果在相容,则几乎必然定理1 . l如果_ n和v _ n均为的后验分布且是相容的，则对于任意的有界连续！函数，有卜（川松） 。
• ( 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
  然后，研究了扩散先验分布下单方程模型参数的贝叶斯估计理论，证明了模型系数的后验分布为多元t分布，模型误差项方差的后验估计为逆gamma分布；根据多元t分布和f分布之间的关系，构造了模型系数线性假设检验的贝叶斯方法；根据hpd置信区间构造了随机误差序列自相关的贝叶斯诊断和单位根检验方法，并利用单方程模型的贝叶斯推断理论研究了方差已知时的贝叶斯均值控制图和方差未知时的贝叶斯均值?标准差控制图。
• As far as the system observation for accuracy evaluation of carrier rocket is concerned , there may exist different types of observed data and priors . heterogeneous information means that the different information describing the different characteristics of the same object . since all of the information is relevant to the same object , the fusion is possible . it is a key problem that how to fuse the heterogeneous information to obtain the better evaluation result . therefore , the different heterogeneous information and data is thoroughly studied , moreover , the mathematical description for information fusion of different parameter priors and data is constructed in this paper . based on their relationship between different parameters , indirect prior and observation data is transformed into prior in impact point observation space , which is fused with original prior by weight determined by maximum entropy rule to obtain the mixed posterior distribution . therefore , the test results can be given by combining posterior distribution and impact error observed data . then its application on evaluating guidance systematic error is elaborated as it applies trajectory tracking data , test value of coefficients of guidance instrumentation systematic error , impact point observation data and prior . especially , the advantage of this method lies in its application in case that guidance instrumentation systematic error may not be computed precisely . finally a detailed example on evaluation of carrier rocket is given to verify the theory
  为充分利用运载火箭观测中的不同观测空间和过程的信息来进行精度评估,针对该背景建立了异质先验融合的数学描述.研究了飞行试验中不同观测空间和过程的异质先验信息和数据,基于不同观测过程的解析关系,将间接过程的先验和观测数据算出的后验分布转换成落点观测空间上的先验,与原落点的先验进行了最大熵加权融合,得到混合后验分布,从而结合落点观测数据给出评定结果.在无法解算出精确的制导工具误差系数的情况下,这种方法充分利用了弹道跟踪数据、工具误差系数的地面测试先验值、落点先验及落点数据,稳健性更好,准确性更高
• ( 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
  通过多方程模型系统的统计结构，证明了矩阵正态? wishart先验分布是模型参数( ， )的共轭先验分布，研究了该先验分布下模型系数矩阵、精度阵和协方差阵的后验分布及其贝叶斯估计，对模型预报密度函数进行了严格的数学推导，并将其应用于多元质量控制领域，构造了贝叶斯均值向量联合控制图；结合wishart分布与x ~ 2分布之间的关系，设计与推断了贝叶斯多指标过程能力指数及其贝叶斯置信下限。
• 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
  第二部分内容是本文应用理论知识的简要阐述，介绍了贝叶斯统计方法的理论，分别说明了先验信息的定义及如何获取，后验分布、条件分布和先验分布三者关系，统计推断方法及贝叶斯统计方法应用的关键。第三部分内容是对坦克射击学中外弹道学的修正理论作了简要的介绍。