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Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML

Approximate standard errors (ASE) of variance components for random regression coefficients are calculated from the average information matrix obtained in a residual maximum likelihood procedure. Linear combinations of those coefficients define variance components for the additive genetic variance a...

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Detalles Bibliográficos
Autores principales: Fischer, Troy M, Gilmour, Arthur R, Werf, Julius HJ van der
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2697206/
https://www.ncbi.nlm.nih.gov/pubmed/15107271
http://dx.doi.org/10.1186/1297-9686-36-3-363
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author Fischer, Troy M
Gilmour, Arthur R
Werf, Julius HJ van der
author_facet Fischer, Troy M
Gilmour, Arthur R
Werf, Julius HJ van der
author_sort Fischer, Troy M
collection PubMed
description Approximate standard errors (ASE) of variance components for random regression coefficients are calculated from the average information matrix obtained in a residual maximum likelihood procedure. Linear combinations of those coefficients define variance components for the additive genetic variance at given points of the trajectory. Therefore, ASE of these components and heritabilities derived from them can be calculated. In our example, the ASE were larger near the ends of the trajectory.
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spelling pubmed-26972062009-06-16 Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML Fischer, Troy M Gilmour, Arthur R Werf, Julius HJ van der Genet Sel Evol Research Approximate standard errors (ASE) of variance components for random regression coefficients are calculated from the average information matrix obtained in a residual maximum likelihood procedure. Linear combinations of those coefficients define variance components for the additive genetic variance at given points of the trajectory. Therefore, ASE of these components and heritabilities derived from them can be calculated. In our example, the ASE were larger near the ends of the trajectory. BioMed Central 2004-05-15 /pmc/articles/PMC2697206/ /pubmed/15107271 http://dx.doi.org/10.1186/1297-9686-36-3-363 Text en Copyright © 2004 INRA, EDP Sciences
spellingShingle Research
Fischer, Troy M
Gilmour, Arthur R
Werf, Julius HJ van der
Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML
title Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML
title_full Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML
title_fullStr Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML
title_full_unstemmed Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML
title_short Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML
title_sort computing approximate standard errors for genetic parameters derived from random regression models fitted by average information reml
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2697206/
https://www.ncbi.nlm.nih.gov/pubmed/15107271
http://dx.doi.org/10.1186/1297-9686-36-3-363
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