Miescke K J, Musa M N
University of Illinois at Chicago.
J Psychiatry Neurosci. 1994 Jul;19(4):295-300.
For a mixture of three normal distributions, which represent genotypes AA, Aa and aa, a method of estimation of the seven unknown parameters is proposed which works well whenever the phenotype (aa) is sufficiently well separated from the phenotype (AA, Aa). It is based on p-values of Kolmogorov's test of goodness of fit to normality. Initial parameter values for this iterative algorithm can be found by visual check and/or by using the EM algorithm. In an example of a data set of size 59 from a study of the metabolic rate of desipramine, the usefulness of this method is demonstrated. Extensions to more complex situations are feasible and are indicated at the end.
对于由代表基因型AA、Aa和aa的三个正态分布组成的混合分布,本文提出了一种估计七个未知参数的方法。只要表型(aa)与表型(AA、Aa)充分分离,该方法就能很好地发挥作用。它基于对正态性拟合优度的柯尔莫哥洛夫检验的p值。这种迭代算法的初始参数值可以通过目视检查和/或使用期望最大化(EM)算法来找到。在一个来自地昔帕明代谢率研究的大小为59的数据集示例中,证明了该方法的有效性。扩展到更复杂的情况是可行的,并且在文末有所提及。