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通过期望最大化(EM)算法将混合模型拟合到分组和截断数据。

Fitting mixture models to grouped and truncated data via the EM algorithm.

作者信息

McLachlan G J, Jones P N

机构信息

Department of Mathematics, University of Queensland, St. Lucia, Australia.

出版信息

Biometrics. 1988 Jun;44(2):571-8.

PMID:3390510
Abstract

The fitting of finite mixture models via the EM algorithm is considered for data which are available only in grouped form and which may also be truncated. A practical example is presented where a mixture of two doubly truncated log-normal distributions is adopted to model the distribution of the volume of red blood cells in cows during recovery from anemia.

摘要

对于仅以分组形式提供且可能被截断的数据,考虑通过期望最大化(EM)算法拟合有限混合模型。给出了一个实际例子,其中采用两个双截断对数正态分布的混合来模拟奶牛从贫血恢复过程中红细胞体积的分布。

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