This paper presents a unified approach to the problem of best linear unbiased prediction (BLUP) of a joint vector of all unknown parameters in a general linear random-effects model (LRM) with restrictions and new observations via some state-of-the-art tools in matrix mathematics. We first establish the fundamental matrix equation and the exact algebraic expression for calculating the Best Linea...

In this research genetic and phenotypic parameters were estimated using linear and threshold models, for reproductive traits, data from 6 large industrial dairy herd of East Azerbaijan province collected by Agriculture Jihad Organization during 10 years (2001-2010). Best linear unbiased predictions of traits breeding values were estimated using Restricted Maximum Likelihood method by WOMBAT sof...

In this research genetic and phenotypic parameters were estimated using linear and threshold models, for reproductive traits, data from 6 large industrial dairy herd of East Azerbaijan province collected by Agriculture Jihad Organization during 10 years (2001-2010). Best linear unbiased predictions of traits breeding values were estimated using Restricted Maximum Likelihood method by WOMBAT sof...

The minimum mean squared error (MMSE) criterion is a popular criterion for devising best predictors. In case of linear predictors, it has the advantage that no further distributional assumptions need to be made, other then about the firstand second-order moments. In the spatial and Earth sciences, it is the best linear unbiased predictor (BLUP) that is used most often. Despite the fact that in ...

Nearly all estimators in statistical prediction come with an associated tuning parameter, in one way or another. Common practice, given data, is to choose the tuning parameter value that minimizes a constructed estimate of the prediction error of the estimator; we focus on Stein’s unbiased risk estimator, or SURE (Stein, 1981; Efron, 1986), which forms an unbiased estimate of the prediction err...

In this paper, we propose the weighted moments estimators (WMEs) of the scale parameter of a Pareto distribution with known shape parameter under the type II multiply censored sample. Moreover, we give a computational comparison for these proposed WMEs and best linear unbiased estimator (BLUE) of the scale parameter on the basis of the exact mean squared error (MSE) for given sample sizes and d...

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...