Multivariable Dispersed Reply Model on Maximum Likelihood Estimate Method

机译：最大似然估计方法的多变量分散答复模型

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To appraisal of the multi-dimensional probability density, mostly using numerical integration and MCMC value optimization method. Like this not only makes the computation load to be big, moreover, when the integral number of times is high, is quite difficult regarding the actual data analysis. This research's goal is gives the probability density function approximate formula of the generalized linearity mixed model, with this formula regarding the multivariable discrete distribution's extrapolation question and carries on the analysis well.

机译：要评估多维概率密度，通常使用数值积分和MCMC值优化方法。这样不仅使计算量大，而且，在整数倍高时，对于实际数据分析来说是相当困难的。本研究的目的是给出广义线性混合模型的概率密度函数近似公式，该公式针对多变量离散分布的外推问题并进行很好的分析。

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《International institute of statistics and management engineering symposium》|2010年|p.587-589|共3页
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XIONG Guojing;
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正文语种
中图分类管理学;管理学;
关键词
maximum likelihood estimate; probability density; mixed model; analysis;

机译：最大似然估计;概率密度混合模型分析;

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Multivariable Dispersed Reply Model on Maximum Likelihood Estimate Method

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