An application of Gibbs sampling in animal breeding is carried out using two different types of prior specification. The first specification has full conjugacy and the second one has non-conjugacy, which causes computational difficulties. This paper demonstrates how the Gibbs sampling procedure, making use of an adaptive rejection sampling algorithm, deals with non-conjugacy in animal breeding using a balanced one-way classification with a random sire effects model and compares the results of two different specifications. It is also shown how Bayesian methods solve the problem of obtaining a negative estimated variance
A crucial problem in Bayesian posterior computation is efficient sampling from a univariate distribu...
Data available in animal breeding are often subject to selection. Such data can be viewed as data w...
A method for the detection of segregating major genes based on the analysis of estimated marginal po...
The application of Gibbs sampling is considered for inference in a mixed inheritance model in animal...
This article proposes the Bayesian approach to solve problems arising in animal breeding theory. Gen...
Abstract Background In the genetic analysis of binary traits with one observation per animal, animal...
Abstract Simulated data were used to investigate the influence of the choice of priors on estimation...
In the case of the mixed linear model the random effects are usually assumed to be normally distribu...
Markov chain Monte-Carlo methods are increasingly being applied to make inferences about the margina...
This paper summarizes some basic principles and concepts of Bayesian analysis in animal breeding app...
Statistics uses two major approaches- conventional (or frequentist) and Bayesian approach. Bayesian ...
Abstract Background Accounting for and quantifying the associative effect of each animal could impro...
A comprehensive review of history and use of methods for estimating variance components is given and...
Bayesian (via Gibbs sampling) and empirical BLUP (EBLUP) estimation of fixed effects and breeding va...
A sire evaluation procedure is proposed for situations in which there is uncertainty with respect to...
A crucial problem in Bayesian posterior computation is efficient sampling from a univariate distribu...
Data available in animal breeding are often subject to selection. Such data can be viewed as data w...
A method for the detection of segregating major genes based on the analysis of estimated marginal po...
The application of Gibbs sampling is considered for inference in a mixed inheritance model in animal...
This article proposes the Bayesian approach to solve problems arising in animal breeding theory. Gen...
Abstract Background In the genetic analysis of binary traits with one observation per animal, animal...
Abstract Simulated data were used to investigate the influence of the choice of priors on estimation...
In the case of the mixed linear model the random effects are usually assumed to be normally distribu...
Markov chain Monte-Carlo methods are increasingly being applied to make inferences about the margina...
This paper summarizes some basic principles and concepts of Bayesian analysis in animal breeding app...
Statistics uses two major approaches- conventional (or frequentist) and Bayesian approach. Bayesian ...
Abstract Background Accounting for and quantifying the associative effect of each animal could impro...
A comprehensive review of history and use of methods for estimating variance components is given and...
Bayesian (via Gibbs sampling) and empirical BLUP (EBLUP) estimation of fixed effects and breeding va...
A sire evaluation procedure is proposed for situations in which there is uncertainty with respect to...
A crucial problem in Bayesian posterior computation is efficient sampling from a univariate distribu...
Data available in animal breeding are often subject to selection. Such data can be viewed as data w...
A method for the detection of segregating major genes based on the analysis of estimated marginal po...