Empirical estimates of the accuracy breeding values (EBV) can be obtained by cross-validation. Leave-one-out cross-validation (LOOCV) is an extreme case k-fold Efficient strategies for LOOCV predictions phenotypes have been developed a simple model with overall mean and random marker or animal genetic effects. The objective here was to develop evaluate efficient method prediction other effects ...

The classical unbiasedness condition utilized e.g. by the best linear unbiased estimator (BLUE) is very stringent. By softening the ”global” unbiasedness condition and introducing component-wise conditional unbiasedness conditions instead, the number of constraints limiting the estimator’s performance can in many cases significantly be reduced. In this paper we extend the findings on the compon...

We introduce MC+, a fast, continuous, nearly unbiased, and accurate method of penalized variable selection in high-dimensional linear regression. The LASSO is fast and continuous, but biased. The bias of the LASSO interferes with variable selection. Subset selection is unbiased but computationally costly. The MC+ has two elements: a minimax concave penalty (MCP) and a penalized linear unbiased ...

Single-step genomic best linear unbiased predictor (ssGBLUP) is a methodology for estimating breeding values jointly genotyped and non-genotyped animals. Since its development in the early 2010s, ssGBLUP faced challenges like modelling missing pedigrees, efficiently computing accuracies, ensuring compatibility between pedigree information, implementing large-scale genetic evaluations, using ani...