No. 31 (2008)
Articles

Estimating Genetic Parameters using a Random Regression Model

Published November 24, 2008
Szilárd Márkus
Debreceni Egyetem Agrár- és Műszaki Tudományok Centruma, Mezőgazdaságtudományi Kar, Debrecen
Eva Němcová
Research Institute of Animal Production, Prága-Uhříněves, Csehország
István Fazekas
Debreceni Egyetem Informatikai Kar, Alkalmazott Matematika és Valószínűségszámítás Tanszék, Debrecen
István Komlósi
Debreceni Egyetem Agrár- és Műszaki Tudományok Centruma, Mezőgazdaságtudományi Kar, Debrecen
pdf

APA

Márkus, S., Němcová, E., Fazekas, I., & Komlósi, I. (2008). Estimating Genetic Parameters using a Random Regression Model. Acta Agraria Debreceniensis, (31), 53-55. https://doi.org/10.34101/actaagrar/31/3006

One of the most important part of the genetic evaluation using a random regression model is the estimation of variance components. This is the topic of many papers because the large computational costs. We can use restricted maximum likelihood (REML), Gibbs sampling and ℜ method for the estimation of genetic parameters. The variance components are necessary to calculate the heritabilities and repeatabilities.
The aim of our paper is to estimate the variance components using a random regression repeatability model from test day data set of Hungarian Holstein-Friesian dairy cows and to analyse the change of additive genetic and permanent environmental variance, heritability and repeatability over lactation.

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