On Information Rank Deficiency in Phenotypic Covariance Matrices.

ABSTRACT: This article investigates a form of rank deficiency in phenotypic covariance matrices derived from geometric morphometric data, and its impact on measures of phenotypic integration. We first define a type of rank deficiency based on information theory then demonstrate that this deficiency impairs the performance of phenotypic integration metrics in a model system. Lastly, we propose methods to treat for this information rank deficiency. Our first goal is to establish how the rank of a typical geometric morphometric covariance matrix relates to the information entropy of its eigenvalue spectrum. This requires clear definitions of matrix rank, of which we define three: the full matrix rank (equal to the number of input variables), the mathematical rank (the number of nonzero eigenvalues), an

SUBMITTER: O'Keefe FR 

PROVIDER: S-EPMC9203068 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature