In the small area estimation, empirical best linear unbiased predictor (EBLUP) in mixed model is useful because it gives a stable estimate for mean of area. For measuring uncertainty EBLUP, much research focused on second-order estimation squared prediction errors univariate case. this paper, we consider multivariate Fay–Herriot where covariance matrix random effects fully unknown, and obtain c...

the objective of this study was to compare six statistical methods for prediction of genomic breedingvalues for traits with different genetic architecture in term of gene effects distributions and number ofquantitative traits loci (qtls). a genome consisted of 500 bi-allelic single nucleotide polymorphism(snp) markers distributed over a chromosomes with 100 cm length was simulated. three differ...

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 ...

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...

Linear regression models that include random effects are commonly used to analyze longitudinal and correlated data. Assume that a general linear random-effects model y = Xβ + ε with β = Aα+γ is given, and new observations in the future follow the linear model yf = Xfβ +εf . This paper shows how to establish a group of matrix equations and analytical formulas for calculating the best linear unbi...

The objective of the present study was to estimate genetic trends for lactation milk yield, persistency of milk yield, somatic cell count and interval between first and second calving in Holstein dairy cows of Iran. The dataset consisted of 210,625 test day and 25,883 first parity cows with milk yield recorded from July 2002 to September 2007 comprising 97 herds in Iran. Breeding values of anim...