似然函数

词组短语

likelihood function

与似然函数相关的网络例句 [注：此内容来源于网络，仅供参考]

According to its statistical structure of likelihood function, constructed their Bayesian estimation under the normal-Gamma conjugate prior distribution.

首先，从最简单的时间序列AR模型入手，分析了时间序列AR模型的统计结构及其条件似然函数，根据似然函数构造了模型参数的共轭先验分布。

The maximum likelihood function of the fatigue life was proposed based on the maximum likelihood principle, and it was born out that the maximum likelihood method could be used for the fatigue analysis.

基于极大似然原理，推导出关于疲劳寿命的极大似然函数，并证明了将极大似然方法用于疲劳分析的可行性。

This paper proposes a new cost function which is based on the likelihood function amplified with a nonlinear function, and the global convergence of this function can be obtained more easily than the original cost function.

本文从参数的最大似然估计出发，采用非线性来放大似然函数并构造一个新的代价函数，该函数能更明显区分局部和全局最佳值。

A maximum likelihood method for the parameter estimation of the delay time model based on observed data is established in this paper.

介绍了基于客观数据的延迟时间模型参数极大似然估计方法，提出了应用优化理论中的单纯形法求解似然函数的算法，为延迟时间模型的参数估计问题提供了可行的解决方法。

It describes the heteroskedasticity character of interest rate by projecting the sample data onto the EGARCH (1, 1) auxiliary model, makes making the covariance matrix as moment conditions and uses EMM to estimate the parameters. EMM avoids the disadvantage of infeasible or computationally intensive of maximum likelihood functions.

通过将观测数据映射成EGARCH(1， 1)辅助模型描述利率行为的异方差特征，以协方差矩阵为矩条件，用有效矩估计方法得出模型参数，避免了最大似然估计法似然函数不可知或难以求积分的缺陷。

The fourth chapter in this paper introduces the modeling ideas of stochasticvolatility into panel data model and puts forward panel data stochastic volatilitymodel. The Kalman Filtering can be employed to filter out the quasi-likelihoodfunction of the model and quasi-maximum likelihood estimation is used as achief means of estimating the parameter of the model.

第四章则将随机波动建模思想引入平行数据模型，提出平行数据随机波动模型，运用卡尔漫滤波方法得到模型的伪似然函数，进而采用极大似然估计方法求解模型参数。

Firstly, the maximum likelihood criterion is employed to model the multi-view tracking problem. Then, the likelihood function is factorized based on the conditional independent assumptions. Finally, the estimation of the target location in each camera view is obtained by using an efficient message passing mechanism. In our algorithm, image data from all cameras no longer need to be transmitted to and processed by a central unit.

该算法首先利用最大似然准则对多视角目标跟踪问题进行建模，并对似然函数进行分解，最后借助消息传递机制高效求解出跟踪目标在各个摄像机视野中位置的估计值，而不再需要将图像数据传输到中央处理单元进行集中式处理。

Firstly, the maximum likelihood criterion is employed to model the multi-view tracking problem. Then, the likelihood function is factorized based on the conditional independent assumptions.

该算法首先利用最大似然准则对多视角目标跟踪问题进行建模，并对似然函数进行分解，最后借助消息传递机制高效求解出跟踪目标在各个摄像机视野中位置的估计值，而不再需要将图像数据传输到中央处理单元进行集中式处理。

On the approximate uncorrelation property of DWT coefficients of LMSV process in the same scale and different scales, first the quasi maximum likelihood estimation method of parameters and the estimation method of volatility process of LMSV model are presented.

根据小波变换可将过程分解到不同的尺度上以及LMSV过程同一尺度下和不同尺度下DWT系数的近似不相关性，提出了建立局部似然函数的方法，又根据DWT系数和MODWT系数之间的关系，将局部似然函数表示为模型参数和局部小波方差估计的形式，并用该方法对中国股市收益进行了时变LMSV模型参数的估计。

In the training of HMM, referring to the auxiliary function in reference〓, and the method in reference〓 to get the estimations of the parameters of Markov chain, we define the likelihood function and auxiliary function for the maximum likelihood estimation of CDHMM, and then induce systematically the forward-backward algorithm and the re-estimation formulas for parameters of CDHMM.

在HMM的建模方面，本文借鉴文献〓中求多变量观测值马尔可夫链参数时辅助函数的选取方法，定义了CDHMM的似然函数和辅助函数；借鉴文献〓中求解马尔可夫链参数时的求偏导方法，并针对本文辅助函数加以简化和改进，系统地推导了HMM的前向—后向算法，以及CDHMM各参数的极大似然估计公式。

与似然函数相关的网络解释 [注：此内容来源于网络，仅供参考]

discrete distribution：离散分布

这与人们的直观有一定的出入. 后来,有人将hazard函数设定为一种"U"字型的函数,还有人将它设定为Weibull型、Lancaster型. 同时考虑到对象的duration的异质性(heterogeneity),Heckman(1984)又使用离散分布(discrete distribution)近似估计最大似然函数,等等.

linear discriminant function：线形判别函数

likelihood 似然 | linear discriminant function 线形判别函数 | local control 局部控制

function, Legendre：雷建德函数

拉普拉斯机率密度函数 function, Laplace probability density | 雷建德函数 function, Legendre | 似然函数,相似度函数 function, likelhood

Likelihood function：似然函数

费歇尔的似然函数(likelihood function)席卷了整个数理统计学界,迅速成为估计参数的主要方法. 极大似然估计只存在一个问题,就是在试图求解MLE时所涉及的数学问题,其难以对付的程度确实令人望而生畏. 费歇尔的论文里写满了一行又一行的复杂代数式,

partial likelihood function：偏似然函数

偏回归系数|partial regression coefficient | 偏似然函数|partial likelihood function | 偏微分不等式|partial differential inequality

partial likelihood function：部分似然函数

partial correlation coefficient 偏相关系数 | partial likelihood function 部分似然函数 | partial regression coefficient 偏回归系数

marginal likelihood function：边缘似然函数

边缘链|boundary chain | 边缘似然函数|marginal likelihood function | 边缘同态|boundary homomorphism

limacon：蚶线,蛃牛形曲线

likelihood function 似然函数 | limacon 蚶线,蛃牛形曲线 | limb of electro-magnet 电磁铁心

conditional Monte Carlo method：条件蒙特卡罗法

conditional log likelihood function 条件对数似然函数 | conditional Monte Carlo method 条件蒙特卡罗法 | conditional name 条件名

penalized likelihood function：罚似然函数

罚函数法||penalty function method | 罚似然函数||penalized likelihood function | 法贝尔-克拉恩不等式||Faber-Krahn inequality