Add to ORKGLet (Y1,θ1),...,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed according to a distribution depending only on θi for i = 1,...,n. In this paper, best linear unbiased predictors (BLUPs) of the θi’s are investigated. We show that BLUPs of θi’s do not exist in certain situations. Furthermore, we present a general empirical Bayes technique for deriving BLUPs. 2000 Mathematics Subject Classification: 62C12. 1. Introduction. Let (Y1,θ1),...,(Yn,θ
The multivariate mixed linear model or multivariate components of variance model with equal replicat...
Let (X1, θ1), (X2, θ2),⋯, (XN, 0N), (XN+1, 0N+1) be independent random vectors with each θi- distrib...
Let (X1, θ1), (X2, θ2),⋯, (XN, 0N), (XN+1, 0N+1) be independent random vectors with each θi- distrib...
Let (Y1,θ1),...,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed ...
Let (Y1,θ1),…,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed ac...
AbstractA linear model with random effects, μi, and random error variances, σi, is considered. The l...
In this article we consider the general linear model {y, X ß, V} where y is the observable random ve...
AbstractA linear model with random effects, μi, and random error variances, σi, is considered. The l...
Assume that in independent two-dimensional random vectors (X1, θ),.., (XN, θN) each θi is distribute...
This paper deals with existence and construction of optimal unbiased statistical predictors. Such pr...
Assume that in independent two-dimensional random vectors (X1, θ),.., (XN, θN) each θi is distribute...
SUMMARY. Let {Xn, n ≥ 1} be a sequence of independent and identically distributed ran-dom variables ...
The minimum mean squared error (MMSE) criterion is a popular criterion for devising best predictors....
In this contribution, we extend the existing theory of minimum mean squared error prediction (best p...
Best linear unbiased estimators (BLUE’s) are known to be optimal in many respects under normal assum...
The multivariate mixed linear model or multivariate components of variance model with equal replicat...
Let (X1, θ1), (X2, θ2),⋯, (XN, 0N), (XN+1, 0N+1) be independent random vectors with each θi- distrib...
Let (X1, θ1), (X2, θ2),⋯, (XN, 0N), (XN+1, 0N+1) be independent random vectors with each θi- distrib...
Let (Y1,θ1),...,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed ...
Let (Y1,θ1),…,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed ac...
AbstractA linear model with random effects, μi, and random error variances, σi, is considered. The l...
In this article we consider the general linear model {y, X ß, V} where y is the observable random ve...
AbstractA linear model with random effects, μi, and random error variances, σi, is considered. The l...
Assume that in independent two-dimensional random vectors (X1, θ),.., (XN, θN) each θi is distribute...
This paper deals with existence and construction of optimal unbiased statistical predictors. Such pr...
Assume that in independent two-dimensional random vectors (X1, θ),.., (XN, θN) each θi is distribute...
SUMMARY. Let {Xn, n ≥ 1} be a sequence of independent and identically distributed ran-dom variables ...
The minimum mean squared error (MMSE) criterion is a popular criterion for devising best predictors....
In this contribution, we extend the existing theory of minimum mean squared error prediction (best p...
Best linear unbiased estimators (BLUE’s) are known to be optimal in many respects under normal assum...
The multivariate mixed linear model or multivariate components of variance model with equal replicat...
Let (X1, θ1), (X2, θ2),⋯, (XN, 0N), (XN+1, 0N+1) be independent random vectors with each θi- distrib...
Let (X1, θ1), (X2, θ2),⋯, (XN, 0N), (XN+1, 0N+1) be independent random vectors with each θi- distrib...