Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae)
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
DOI: | 10.4025/actascitechnol.v36i4.21192 |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/21192 |
Resumo: | The objective of this analysis was to fit germination data of Rhipsalis cereuscula Haw seeds to the Weibull model with three parameters using Frequentist and Bayesian methods. Five parameterizations were compared using the Bayesian analysis to fit a prior distribution. The parameter estimates from the Frequentist method were similar to the Bayesian responses considering the following non-informative a priori distribution for the parameter vectors: gamma (10³, 10³) in the model M1, normal (0, 106) in the model M2, uniform (0, Lsup) in the model M3, exp (μ) in the model M4 and Lnormal (μ, 106) in the model M5. However, to achieve the convergence in the models M4 and M5, we applied the μ from the estimates of the Frequentist approach. The best models fitted by the Bayesian method were the M1 and M3. The adequacy of these models was based on the advantages over the Frequentist method such as the reduced computational efforts and the possibility of comparison. |
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Acta scientiarum. Technology (Online) |
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Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae)Bayesian inferencegrowth curvemodelingProbabilidade e Estatística AplicadasThe objective of this analysis was to fit germination data of Rhipsalis cereuscula Haw seeds to the Weibull model with three parameters using Frequentist and Bayesian methods. Five parameterizations were compared using the Bayesian analysis to fit a prior distribution. The parameter estimates from the Frequentist method were similar to the Bayesian responses considering the following non-informative a priori distribution for the parameter vectors: gamma (10³, 10³) in the model M1, normal (0, 106) in the model M2, uniform (0, Lsup) in the model M3, exp (μ) in the model M4 and Lnormal (μ, 106) in the model M5. However, to achieve the convergence in the models M4 and M5, we applied the μ from the estimates of the Frequentist approach. The best models fitted by the Bayesian method were the M1 and M3. The adequacy of these models was based on the advantages over the Frequentist method such as the reduced computational efforts and the possibility of comparison. Universidade Estadual De Maringá2014-09-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionanálise estatísticaapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/2119210.4025/actascitechnol.v36i4.21192Acta Scientiarum. Technology; Vol 36 No 4 (2014); 651-656Acta Scientiarum. Technology; v. 36 n. 4 (2014); 651-6561806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/21192/pdf_37Guedes, Terezinha AparecidaRossi, Robson MarceloMartins, Ana Beatriz TozzoJaneiro, VanderlyCarneiro, José Walter Pedrozainfo:eu-repo/semantics/openAccess2014-10-29T09:50:03Zoai:periodicos.uem.br/ojs:article/21192Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2014-10-29T09:50:03Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) |
title |
Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) |
spellingShingle |
Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) Guedes, Terezinha Aparecida Bayesian inference growth curve modeling Probabilidade e Estatística Aplicadas Guedes, Terezinha Aparecida Bayesian inference growth curve modeling Probabilidade e Estatística Aplicadas |
title_short |
Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) |
title_full |
Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) |
title_fullStr |
Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) |
title_full_unstemmed |
Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) |
title_sort |
Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae) |
author |
Guedes, Terezinha Aparecida |
author_facet |
Guedes, Terezinha Aparecida Guedes, Terezinha Aparecida Rossi, Robson Marcelo Martins, Ana Beatriz Tozzo Janeiro, Vanderly Carneiro, José Walter Pedroza Rossi, Robson Marcelo Martins, Ana Beatriz Tozzo Janeiro, Vanderly Carneiro, José Walter Pedroza |
author_role |
author |
author2 |
Rossi, Robson Marcelo Martins, Ana Beatriz Tozzo Janeiro, Vanderly Carneiro, José Walter Pedroza |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Guedes, Terezinha Aparecida Rossi, Robson Marcelo Martins, Ana Beatriz Tozzo Janeiro, Vanderly Carneiro, José Walter Pedroza |
dc.subject.por.fl_str_mv |
Bayesian inference growth curve modeling Probabilidade e Estatística Aplicadas |
topic |
Bayesian inference growth curve modeling Probabilidade e Estatística Aplicadas |
description |
The objective of this analysis was to fit germination data of Rhipsalis cereuscula Haw seeds to the Weibull model with three parameters using Frequentist and Bayesian methods. Five parameterizations were compared using the Bayesian analysis to fit a prior distribution. The parameter estimates from the Frequentist method were similar to the Bayesian responses considering the following non-informative a priori distribution for the parameter vectors: gamma (10³, 10³) in the model M1, normal (0, 106) in the model M2, uniform (0, Lsup) in the model M3, exp (μ) in the model M4 and Lnormal (μ, 106) in the model M5. However, to achieve the convergence in the models M4 and M5, we applied the μ from the estimates of the Frequentist approach. The best models fitted by the Bayesian method were the M1 and M3. The adequacy of these models was based on the advantages over the Frequentist method such as the reduced computational efforts and the possibility of comparison. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-09-12 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion análise estatística |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/21192 10.4025/actascitechnol.v36i4.21192 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/21192 |
identifier_str_mv |
10.4025/actascitechnol.v36i4.21192 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/21192/pdf_37 |
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. Technology; Vol 36 No 4 (2014); 651-656 Acta Scientiarum. Technology; v. 36 n. 4 (2014); 651-656 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (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. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1822182870244917248 |
dc.identifier.doi.none.fl_str_mv |
10.4025/actascitechnol.v36i4.21192 |