English translation for "posterior distribution"

后分布
后验分布

Related Translations:

posterior process:  后突,蝶突

posterior arm:  后腕

posterior wall:  后壁

posterior papillary:  后乳头的

posterior lenticonus:  后圆锥形晶状体

posterior tuberosity:  后瘤

posterior orbit:  后眼眶

posterior cornu:  后角突

rachischisis posterior:  脊柱后裂, 脊柱裂

posterior ring:  后环

Example Sentences:

	1.	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。
	2.	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。
	3.	Our proposed approach is to split the dataset sample into two parts and change the strategy of scanning datasets into two loop , the inner loop and the outer loop . the scan of the dataset will become the outer loop and the scan of the draws from the posterior distribution 该算法对数据集进行划分，改变mcmc对数据集的扫描策略，将其分开为内、外两个循环过程，外循环中扫描数据集，内循环扫描分布函数的抽样值。
	4.	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。
	5.	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） 。
	6.	On this basis a nonlinear filtering technique of sequential monte carlo particle filter based on bayesian approach is emphatically disussed which the posterior distribution of the state variables can be represented by a set of weighted particles , so the method base advantages over the above algorithms in robustness and accuracy for nonlinear non - gaussian filtering problems 在此基础上重点论述了一种基于贝叶斯原理的序贯蒙特卡罗粒子滤波技术，该方法通过粒子的加权和表征后验概率密度，获得状态估值，在处理非线性非高斯系统的状态估计问题时精度逼近最优，鲁棒性更好。
	7.	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
	8.	Finally , bayesian fusion algorithm with weibull distribution has been studied in detail by using he - ne laser life test data . , which includes three aspects , that is , the selection of weibull distribution model , the posterior distribution of weibull parameters with multiple a priori information and the dynamic modeling method of weibull distribution parameters under the condition of different test environments 最后,结合he - ne激光器寿命试验数据,重点研究了威布尔分布的bayes融合估计算法,主要包括以下三个方面的问题,即:威布尔分布模型选择、多源验前信息的威布尔分布参数的验后分布、不同环境下的威布尔分布参数的动态建模方法。
	9.	( 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。
	10.	Firstly , the problem of multiple a priori information fusion has been studied under the condition of the same test environment , such as the consistency test of a priori information , the credibility analysis of a priori information , the calculation of credibility with information likelihood rate , the expression of fusion posterior distribution based on the credibility of multiple a priori information 首先,研究了同种环境下多源验前信息的融合问题,如验前信息的相容性检验、验前信息的可信性分析、基于信息似然比的可信度计算、基于多源验前信息可信度的融合验后分布表示等。

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