COUNTING METHODS (EM ALGORITHM) IN HUMAN PEDIGREE ANALYSIS - LINKAGE AND SEGREGATION ANALYSIS
COUNTING METHODS (EM ALGORITHM) IN HUMAN PEDIGREE ANALYSIS - LINKAGE AND SEGREGATION ANALYSIS
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DOI：
10.1111/j.1469-1809.1977.tb02031.x
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发表时间：
1977-01-01
影响因子：
1.9
通讯作者：
OTT, J
中科院分区：
文献类型：
--
作者：
OTT, J
人类系谱数据的可能性可以写成这样一种形式，以便计算导数。这是对链接和分离分析中的各种参数所做的。最大似然估计（MLE）的方程以一种特别明显的形式表示，允许迭代求解。这个过程是对Smith（1957）计数方法的谱系的扩展。所有这些过程都属于不完整数据的一般MLE方法，称为EM算法。
The likelihood of human pedigree data can be written in such a form as to allow the computation of derivatives. This is done for various parameters in linkage and segregation analysis. The equations for the maximum likelihood estimates [MLE] are represented in a particularly appearling form which allows iterative solutions. This process is an extension to pedigrees of Smith''s (1957) counting methods. All these procedures belong to a general class of MLE methods for incomplete data called EM algorithms.