Lange K
Am J Hum Genet. 1983 Jul;35(4):687-94.
The usual likelihood formulations for segregation analysis of a genetic trait ignore both the at-risk but unobservable families and the demographic structure of the surrounding population. Families are not ascertained if, by chance, they have no affected members or if the affected members are not ascertained. Ewens has shown that likelihoods which take into explicit account both unobservable families and demographic parameters lead to the same maximum likelihood estimates of segregation and ascertainment parameters as the usual likelihoods. This paper provides an alternative proof of Ewens' theorem based on the Poisson distribution and simple continuous optimization techniques.
遗传性状分离分析中常用的似然公式忽略了有风险但不可观察的家庭以及周围人群的人口结构。如果家庭偶然没有患病成员，或者患病成员未被确定，则这些家庭不会被纳入研究。尤因斯表明，明确考虑不可观察家庭和人口参数的似然性会得出与通常似然性相同的分离和确定参数的最大似然估计值。本文基于泊松分布和简单的连续优化技术，为尤因斯定理提供了另一种证明。
