Estimation of Variances and Covariances Within the Allowable Parameter Space

Abstract

Two computationally simple methods for estimation of variances and covariances, with estimates always within the allowable parameter space, are presented for multiple traits. Both methods involve transformations of data to convert observations into independent sets of traits. A Monte Carlo simulation comparison of eight methods for estimating variances and covariances was conducted. The two proposed methods compared favorably with a general purpose restricted maximum likelihood method. However, one of the methods was slow to converge and requires additional work to make it more useful.