A penalized likelihood approach to pooling estimates of covariance components from analyses by parts.

Abstract excerpt

Estimates of covariance matrices for numerous traits are commonly obtained by pooling results from a series of analyses of subsets of traits. A penalized maximum-likelihood approach is proposed to combine estimates from part analyses while constraining the resulting overall matrices to be positive definite. In addition, this provides the scope for 'improving' estimates of individual matrices by applying a penalty...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Computational Biology
• Share to Likelihood Functions