NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET Animal models and Integrated Nested Laplace Approximations
نویسندگان
چکیده
Animal models are generalized linear mixed model (GLMM) used in evolutionary biology and animal breeding to identify the genetic part of traits. Integrated Nested Laplace Approximation (INLA) is a methodology for making fast non-sampling based Bayesian inference for hierarchical Gaussian Markov models. In this paper we demonstrate that the INLA methodology can be used for many versions of Bayesian animal models. We analyse animal models for both synthetic case studies and house sparrow population case studies with Gaussian, Binomial and Poisson likelihoods using INLA. Inference results are compared with results using Markov Chain Monte Carlo (MCMC) methods. We also introduce an R package, AnimalINLA, for easy and fast inference for Bayesian Animal models using INLA.
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