Many types of genetic analyses depend on estimates of allele frequencies. We consider the problem of allele-frequency estimation based on data from related individuals. The motivation for this work is data collected on the Hutterites, an isolated founder population, so we focus particularly on the case in which the relationships among the sampled individuals are specified by a large, complex pe...

Let (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.

Introduction Genetic progress in traits of economic importance has been impressive during the past few decades. This has been due to a combination of (1) selection, primarily on additive genetic merit, (2) changes in breed structure, and (3) crossbreeding; the relative importance of these factors varying from species to species. This paper is concerned with the first of these factors and is res...

This paper presents methods to provide an optimal evaluation of the nuclear masses. The techniques used for this purpose come from data assimilation (DA) that allows combining, in an optimal and consistent way, information coming from experiment and from numerical modelling. Using all the available information, it leads to improve not only masses evaluations, but also their uncertainties. Each ...

Most of the available results on optimal block designs for diallel crosses are based on standard linear model assumptions where the general combining ability effects are taken as fixed. In many practical situations, this assumption may not be tenable since often one studies only a sample of inbred lines from a possibly large (hypothetical) population. Recently Ghosh and Das (2003) proposed a ra...

We constraint on computer the best linear unbiased generalized statistics of random field for the best linear unbiased generalized statistics of an unknown constant mean of random field and derive the numerical generalized least-squares estimator of an unknown constant mean of random field. We derive the third constraint of spatial statistics and show that the classic generalized least-squares ...

Traditional direct estimation methods are inefficient for domains of a survey population with small sample sizes. To estimate the domain proportions, we combine estimators and regression-synthetic based on domain-level auxiliary information. For case true propose design-based linear combination that is robust alternative to empirical best unbiased predictor (EBLUP) Fay–Herriot model.
 We i...