Background A random multiple-regression model that simultaneously fit all allele
substitution effects for additive markers or haplotypes as uncorrelated random effects was
proposed for Best Linear Unbiased Prediction, using whole-genome data. Leave-one-out
cross validation can be used to quantify the predictive ability of a statistical model. Methods
Naive application of Leave-one-out cross validation is computationally intensive because
the training and validation analyses need to be repeated n times, once for each observation …