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MCMC strategies for a Bayesian analysis of reaction norm models with unknown covariates
The performance of three versions of the Gibbs sampling algorithm, and of two versions of the Langevin-Hastings algorithm were studied in a specific application involving an analysis of a reaction norm model. Two datasets were simulated using...
Identifiability of parameters and behaviour of MCMC chains: a case study using the reaction norm model
, causing non-identifiability. The reaction norm model with unknown covariates (RNUC) is a model in which unknown environmental effects can be inferred jointly with the remaining parameters. The problem of identifiability of parameters at the level...
Efficiency of alternative MCMC strategies illustrated using the reaction norm model
cost) of six MCMC strategies to sample parameters using simulated data generated with a reaction norm model with unknown covariates as an example. The six strategies are single-site Gibbs updates (SG), single-site Gibbs sampler for updating transformed...
Reaction norm of fertility traits adjusted for protein and fat production level across lactations in Holstein cattle
Integration of epidemiology into the genetic analysis of mastitis in Swedish Holstein
Analysis of Milk Production Traits in Early Lactation Using a Reaction Norm Model with Unknown Covariates
The reaction norm model is becoming a popular approach to study genotype x environment interaction (GxE), especially when there is a continuum of environmental effects. These effects are typically unknown, and an approximation that is used...