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A Derivative-Free Approach for Estimating Variance Components in Animal Models by Restricted Maximum Likelihood1
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1987
Year
Parameter EstimationEngineeringBase PopulationsLog LikelihoodRestricted Maximum Likelihood1Animal ModelsDerivative-free AlgorithmBiostatisticsPublic HealthEstimation TheoryPrincipal Component AnalysisStatistical ModelingStatisticsBayesian Hierarchical ModelingVariance ComponentsStatistical GeneticsDerivative-free ApproachFunctional Data AnalysisBiologyHigh-dimensional MethodEvolutionary BiologyStatistical InferenceAnimal BehaviorApproximate Bayesian Computation
A derivative-free algorithm for use in restricted maximum likelihood variance component estimation for single traits and single records in animal or reduced animal models is presented. The algorithm does not require matrix inversion; instead, it uses a one-dimensional search involving the variant part of the log likelihood to find the maximum of this function. An approach to account for selection in base populations is also presented. Sample results are given.