Copula Integration for Genetic Parameter Estimation in Bivariate Linear Mixed Models - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Conference Poster Year : 2024

Copula Integration for Genetic Parameter Estimation in Bivariate Linear Mixed Models

Abstract

In the bivariate gene9c animal model, the es9ma9on methods assume that the traits are gaussian, but in prac9ce, the joint distribu9on of the two traits can be non-Gaussian. This induces a bias in the gene9c parameters es9ma9on when the reproducers are non-randomly selected. The aim of this project was to integrate copula func9ons, characterising the joint distribu9on, in the es9ma9on of gene9c parameters, and so, reduce this bias.
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Dates and versions

hal-04633406 , version 1 (03-07-2024)

Identifiers

  • HAL Id : hal-04633406 , version 1

Cite

Victoria Bruning, Estelle Kuhn, Tom Rohmer. Copula Integration for Genetic Parameter Estimation in Bivariate Linear Mixed Models. Journées Statistiques du Sud 2024, Jun 2024, Toulouse, France. ⟨hal-04633406⟩
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