Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966

Detalhes bibliográficos
Autor(a) principal: Ferreira, Adesio
Data de Publicação: 2008
Outros Autores: Cruz, Cosme Damião, Vasconcelos, Edmar Soares de, Nascimento, Moysés, Ribeiro, Márcio Fernando, Silva, Marcia Flores da
Tipo de documento: Artigo
Idioma: por
Título da fonte: Acta Scientiarum. Agronomy (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5966
Resumo: This study was conducted to propose the use of the empirical nonparametric bootstrap procedure in order to test the significance of the correlations. Eight different population sizes and 10 characteristics were simulated at different correlation levels in each population. The efficiency of the bootstrap method was evaluated by comparing the results of the method, relative to a t-test. The bootstrap method provided identical results to those obtained by the t-test at 1% probability, for the population sizes of 25; 50; 100; 250; 500; 2500 and 5000, therefore showing the adequacy of 5,000 replicas. In general, the effectiveness of the bootstrap was not compromised by the size of the sample under study. The method showed high reliability, in addition to being an appropriate and useful procedure to be adopted in testing the significance of both genotypic and environmental correlations for the genetic improvement of multiple characteristics. The study of the correlation magnitudes that provided both type I and type II errors in all populations reveal the bootstrap method to be appropriate not only for testing the genetic and environmental significances of the correlations, but also in testing phenotypic correlations.
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spelling Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966Utilização de bootstrap não-paramétrico para avaliação de correlações fenotípicas, genotípicas e ambientais - DOI: 10.4025/actasciagron.v30i5.5966genetic improvementsignificance testsintensive computationmelhoramento genéticotestes de significânciacomputação intensivaThis study was conducted to propose the use of the empirical nonparametric bootstrap procedure in order to test the significance of the correlations. Eight different population sizes and 10 characteristics were simulated at different correlation levels in each population. The efficiency of the bootstrap method was evaluated by comparing the results of the method, relative to a t-test. The bootstrap method provided identical results to those obtained by the t-test at 1% probability, for the population sizes of 25; 50; 100; 250; 500; 2500 and 5000, therefore showing the adequacy of 5,000 replicas. In general, the effectiveness of the bootstrap was not compromised by the size of the sample under study. The method showed high reliability, in addition to being an appropriate and useful procedure to be adopted in testing the significance of both genotypic and environmental correlations for the genetic improvement of multiple characteristics. The study of the correlation magnitudes that provided both type I and type II errors in all populations reveal the bootstrap method to be appropriate not only for testing the genetic and environmental significances of the correlations, but also in testing phenotypic correlations.O objetivo deste trabalho foi propor a utilização do procedimento empírico de bootstrap não-paramétrico para testar a significância de correlações. Foram simulados oito diferentes tamanhos de população e dez características, em cada população, com diferentes níveis de correlações. Avaliou-se a eficiência do método bootstrap por meio da comparação dos resultados do método em relação ao teste t. O método bootstrap proporcionou resultados idênticos aos obtidos pelo teste t a 1% de probabilidade, para as populações de tamanho 25, 50, 100, 250, 500, 2.500 e 5.000, demonstrando a adequabilidade de 5.000 réplicas. Em geral, a eficácia do bootstrap não foi comprometida pelo tamanho da amostra estudada. O método apresentou alta confiabilidade e presta-se como procedimento adequado e útil que pode ser adotado para testar a significância de correlações genotípicas e ambientais para fins de melhoramento genético de múltiplas características. O estudo das magnitudes das correlações que proporcionaram os erros tipo I e tipo II, em todas as populações, revela que, em programas de melhoramento de plantas, o método bootstrap é adequado não só para testar as significâncias de correlações genéticas e ambientais, mas também para testar as correlações fenotípicas.Universidade Estadual de Maringá2008-12-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/596610.4025/actasciagron.v30i5.5966Acta Scientiarum. Agronomy; Vol 30 No 5 (2008): Special suplemment; 657-663Acta Scientiarum. Agronomy; v. 30 n. 5 (2008): Suplemento Especial; 657-6631807-86211679-9275reponame:Acta Scientiarum. Agronomy (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMporhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5966/5966Ferreira, AdesioCruz, Cosme DamiãoVasconcelos, Edmar Soares deNascimento, MoysésRibeiro, Márcio FernandoSilva, Marcia Flores dainfo:eu-repo/semantics/openAccess2022-11-23T18:38:14Zoai:periodicos.uem.br/ojs:article/5966Revistahttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgronPUBhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/oaiactaagron@uem.br||actaagron@uem.br|| edamasio@uem.br1807-86211679-9275opendoar:2022-11-23T18:38:14Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966
Utilização de bootstrap não-paramétrico para avaliação de correlações fenotípicas, genotípicas e ambientais - DOI: 10.4025/actasciagron.v30i5.5966
title Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966
spellingShingle Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966
Ferreira, Adesio
genetic improvement
significance tests
intensive computation
melhoramento genético
testes de significância
computação intensiva
title_short Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966
title_full Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966
title_fullStr Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966
title_full_unstemmed Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966
title_sort Use of the nonparametric bootstrap in evaluating genotypic, phenotypic and environmental correlations - DOI: 10.4025/actasciagron.v30i5.5966
author Ferreira, Adesio
author_facet Ferreira, Adesio
Cruz, Cosme Damião
Vasconcelos, Edmar Soares de
Nascimento, Moysés
Ribeiro, Márcio Fernando
Silva, Marcia Flores da
author_role author
author2 Cruz, Cosme Damião
Vasconcelos, Edmar Soares de
Nascimento, Moysés
Ribeiro, Márcio Fernando
Silva, Marcia Flores da
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Ferreira, Adesio
Cruz, Cosme Damião
Vasconcelos, Edmar Soares de
Nascimento, Moysés
Ribeiro, Márcio Fernando
Silva, Marcia Flores da
dc.subject.por.fl_str_mv genetic improvement
significance tests
intensive computation
melhoramento genético
testes de significância
computação intensiva
topic genetic improvement
significance tests
intensive computation
melhoramento genético
testes de significância
computação intensiva
description This study was conducted to propose the use of the empirical nonparametric bootstrap procedure in order to test the significance of the correlations. Eight different population sizes and 10 characteristics were simulated at different correlation levels in each population. The efficiency of the bootstrap method was evaluated by comparing the results of the method, relative to a t-test. The bootstrap method provided identical results to those obtained by the t-test at 1% probability, for the population sizes of 25; 50; 100; 250; 500; 2500 and 5000, therefore showing the adequacy of 5,000 replicas. In general, the effectiveness of the bootstrap was not compromised by the size of the sample under study. The method showed high reliability, in addition to being an appropriate and useful procedure to be adopted in testing the significance of both genotypic and environmental correlations for the genetic improvement of multiple characteristics. The study of the correlation magnitudes that provided both type I and type II errors in all populations reveal the bootstrap method to be appropriate not only for testing the genetic and environmental significances of the correlations, but also in testing phenotypic correlations.
publishDate 2008
dc.date.none.fl_str_mv 2008-12-10
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5966
10.4025/actasciagron.v30i5.5966
url http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5966
identifier_str_mv 10.4025/actasciagron.v30i5.5966
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5966/5966
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Estadual de Maringá
publisher.none.fl_str_mv Universidade Estadual de Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Agronomy; Vol 30 No 5 (2008): Special suplemment; 657-663
Acta Scientiarum. Agronomy; v. 30 n. 5 (2008): Suplemento Especial; 657-663
1807-8621
1679-9275
reponame:Acta Scientiarum. Agronomy (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta Scientiarum. Agronomy (Online)
collection Acta Scientiarum. Agronomy (Online)
repository.name.fl_str_mv Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv actaagron@uem.br||actaagron@uem.br|| edamasio@uem.br
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