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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...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2004
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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. |
format | Text |
id | pubmed-2697206 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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