A computationally efficient algorithm to leverage average information REML for (co)variance component estimation in the genomic era
Abstract Background Methods for estimating variance components (VC) using restricted maximum likelihood (REML) typically require elements from the inverse of the coefficient matrix of the mixed model slate vcc equations (MME).As genomic information becomes more prevalent, the coefficient matrix of the MME becomes denser, presenting a challenge for