Parameter estimation in selected populations with missing data
This study proposes a procedure to estimate genetic parameters in populations where a selection process results in the loss of an unknown number of observations. The method was developed under the Bayesian inference scope following the missing data theory approach. Its implementation requires slight modifications to the Gibbs sampler algorithm. In order to show the efficiency of this option, a simulation study was conducted. © 2009 Blackwell Verlag, Berlin.
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Format: | journal article biblioteca |
Language: | English |
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Wiley
2009
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Subjects: | Bayesian, Estimation, Selection, |
Online Access: | http://hdl.handle.net/20.500.12792/4780 http://hdl.handle.net/10261/294762 |
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dig-inia-es-10261-2947622023-02-20T10:41:49Z Parameter estimation in selected populations with missing data Yagüe-Utrilla, G. García Cortes, Luis Alberto Silander, M. Varona, L. Altarriba, J. Moreno, C. Bayesian Estimation Selection This study proposes a procedure to estimate genetic parameters in populations where a selection process results in the loss of an unknown number of observations. The method was developed under the Bayesian inference scope following the missing data theory approach. Its implementation requires slight modifications to the Gibbs sampler algorithm. In order to show the efficiency of this option, a simulation study was conducted. © 2009 Blackwell Verlag, Berlin. 2023-02-20T10:41:49Z 2023-02-20T10:41:49Z 2009 journal article Journal of Animal Breeding and Genetics 126(2): 103-109 (2009) 0931-2668 http://hdl.handle.net/20.500.12792/4780 http://hdl.handle.net/10261/294762 10.1111/j.1439-0388.2008.00778.x 1439-0388 en none Wiley |
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Bayesian Estimation Selection Bayesian Estimation Selection |
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Bayesian Estimation Selection Bayesian Estimation Selection Yagüe-Utrilla, G. García Cortes, Luis Alberto Silander, M. Varona, L. Altarriba, J. Moreno, C. Parameter estimation in selected populations with missing data |
description |
This study proposes a procedure to estimate genetic parameters in populations where a selection process results in the loss of an unknown number of observations. The method was developed under the Bayesian inference scope following the missing data theory approach. Its implementation requires slight modifications to the Gibbs sampler algorithm. In order to show the efficiency of this option, a simulation study was conducted. © 2009 Blackwell Verlag, Berlin. |
format |
journal article |
topic_facet |
Bayesian Estimation Selection |
author |
Yagüe-Utrilla, G. García Cortes, Luis Alberto Silander, M. Varona, L. Altarriba, J. Moreno, C. |
author_facet |
Yagüe-Utrilla, G. García Cortes, Luis Alberto Silander, M. Varona, L. Altarriba, J. Moreno, C. |
author_sort |
Yagüe-Utrilla, G. |
title |
Parameter estimation in selected populations with missing data |
title_short |
Parameter estimation in selected populations with missing data |
title_full |
Parameter estimation in selected populations with missing data |
title_fullStr |
Parameter estimation in selected populations with missing data |
title_full_unstemmed |
Parameter estimation in selected populations with missing data |
title_sort |
parameter estimation in selected populations with missing data |
publisher |
Wiley |
publishDate |
2009 |
url |
http://hdl.handle.net/20.500.12792/4780 http://hdl.handle.net/10261/294762 |
work_keys_str_mv |
AT yagueutrillag parameterestimationinselectedpopulationswithmissingdata AT garciacortesluisalberto parameterestimationinselectedpopulationswithmissingdata AT silanderm parameterestimationinselectedpopulationswithmissingdata AT varonal parameterestimationinselectedpopulationswithmissingdata AT altarribaj parameterestimationinselectedpopulationswithmissingdata AT morenoc parameterestimationinselectedpopulationswithmissingdata |
_version_ |
1767603655717945344 |