Dairy cattle evaluation schemes routinely assume homogeneous variance with respect to environment. Increasing evidence suggests the presence of systematic changes in variance components associated with mean level of performance. Best linear unbiased prediction procedures that account for heterogeneity are reviewed. The consequences of incorrectly assuming homogeneity for evaluation are demonstr...

Increased use of remotely sensed data is a key strategy adopted by the Forest Inventory and Analysis Program. However, multiple sensor technologies require complex sampling units and sampling designs. The Recursive Restriction Estimator (RRE) accommodates this complexity. It is a design-consistent Empirical Best Linear Unbiased Prediction for the state-vector, which contains all suffi cient sta...

The objective of this study was to assess the efficiency of a modification of the simulated individual best linear unbiased prediction (BLUPIS) procedure, which is used for the approximation of classic individuals (BLUPI) for selection between and within sugarcane families. A total of 110 full-sib families were employed in an experiment initiated in 2007 using a randomized block design with fiv...

The most obvious piece of phenotypic information we can use to estimate an animal’s breeding value is the animal’s own phenotype. But we can also use information from relatives, such as the sire, the dam, siblings and progeny. Commercial genetic evaluation systems produce EBVs for each animal for all traits of relevance. Such an evaluation is based on a statistical procedure leading to Best Lin...

A nonlinear wavelet shrinkage estimator was proposed in Huang and Lu (2000). Such an estimator combined the asymptotic equivalence to the best linear unbiased prediction and the Bayesian estimation in nonparametric mixed-effects models. In this article a data-driven GCV method is proposed to select hyperparameters. The proposed GCV method has low computational cost and can be applied to one or ...

Although markers identified by genome-wide association studies have individually strong statistical significance, their performance in prediction remains limited. Our goal was to use animal breeding genomic prediction models to predict additive genetic contributions for systolic blood pressure (SBP) using whole genome sequencing data with different validation designs. The additive genetic contr...

<p style='text-indent:20px;'>This paper considers simultaneous optimal prediction and estimation problems in the context of linear random-effects models. Assume a pair seemingly unrelated models (SULREMs) with error terms correlated. Our aim is to find analytical formulas for calculating best unbiased predictors (BLUPs) all unknown parameters two by means solving constrained quadratic mat...