Approximate Solutions for the Maximum-Likelihood Estimates
in Models of Univariate Human Twin Data
Wijesiri UW, Williams CJ
Department of Mathematics and Statistics, University of Idaho, Moscow 83843, USA.
Behavior Genetics, 25(3):211-216 (1995)
Abstract
We present numerical results concerning the accuracy of approximate
maximum-likelihood estimators of variance components for several models of univariate
human twin data. The approximations are obtained via a spectral decomposition of the
twin model covariance matrix. The results apply to likelihood functions for univariate
twin data based on either the Wishart distribution or the bivariate normal distribution.
For sample sizes of 100 twin pairs for each zygosity group, if the difference of the traces
of the sample covariance matrices is 10% or less of the sum of the traces, the
approximate solutions can be used as the maximum-likelihood estimators for some
models.
Variance component linkage analysis