Improved Bayes estimators and prediction for the Wilson-Hilferty distribution
Main Author: | |
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Publication Date: | 2019 |
Other Authors: | , , |
Format: | Article |
Language: | eng |
Source: | Anais da Academia Brasileira de Ciências (Online) |
Download full: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500202 |
Summary: | Abstract: In this paper, we revisit the Wilson-Hilferty distribution and presented its mathematical properties such as the r-th moments and reliability properties. The parameters estimators are discussed using objective reference Bayesian analysis for both complete and censored data where the resulting marginal posterior intervals have accurate frequentist coverage. A simulation study is presented to compare the performance of the proposed estimators with the frequentist approach where it is observed a clear advantage for the Bayesian method. Finally, the proposed methodology is illustrated on three real datasets. |
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Improved Bayes estimators and prediction for the Wilson-Hilferty distributionBayesian analysisBayesian predictioncensored dataobjective priorWilson-Hilferty distribution.Abstract: In this paper, we revisit the Wilson-Hilferty distribution and presented its mathematical properties such as the r-th moments and reliability properties. The parameters estimators are discussed using objective reference Bayesian analysis for both complete and censored data where the resulting marginal posterior intervals have accurate frequentist coverage. A simulation study is presented to compare the performance of the proposed estimators with the frequentist approach where it is observed a clear advantage for the Bayesian method. Finally, the proposed methodology is illustrated on three real datasets.Academia Brasileira de Ciências2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500202Anais da Academia Brasileira de Ciências v.91 n.3 2019reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201920190002info:eu-repo/semantics/openAccessRAMOS,PEDRO L.ALMEIDA,MARCO P.TOMAZELLA,VERA L.D.LOUZADA,FRANCISCOeng2019-08-14T00:00:00Zoai:scielo:S0001-37652019000500202Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2019-08-14T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Improved Bayes estimators and prediction for the Wilson-Hilferty distribution |
title |
Improved Bayes estimators and prediction for the Wilson-Hilferty distribution |
spellingShingle |
Improved Bayes estimators and prediction for the Wilson-Hilferty distribution RAMOS,PEDRO L. Bayesian analysis Bayesian prediction censored data objective prior Wilson-Hilferty distribution. |
title_short |
Improved Bayes estimators and prediction for the Wilson-Hilferty distribution |
title_full |
Improved Bayes estimators and prediction for the Wilson-Hilferty distribution |
title_fullStr |
Improved Bayes estimators and prediction for the Wilson-Hilferty distribution |
title_full_unstemmed |
Improved Bayes estimators and prediction for the Wilson-Hilferty distribution |
title_sort |
Improved Bayes estimators and prediction for the Wilson-Hilferty distribution |
author |
RAMOS,PEDRO L. |
author_facet |
RAMOS,PEDRO L. ALMEIDA,MARCO P. TOMAZELLA,VERA L.D. LOUZADA,FRANCISCO |
author_role |
author |
author2 |
ALMEIDA,MARCO P. TOMAZELLA,VERA L.D. LOUZADA,FRANCISCO |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
RAMOS,PEDRO L. ALMEIDA,MARCO P. TOMAZELLA,VERA L.D. LOUZADA,FRANCISCO |
dc.subject.por.fl_str_mv |
Bayesian analysis Bayesian prediction censored data objective prior Wilson-Hilferty distribution. |
topic |
Bayesian analysis Bayesian prediction censored data objective prior Wilson-Hilferty distribution. |
description |
Abstract: In this paper, we revisit the Wilson-Hilferty distribution and presented its mathematical properties such as the r-th moments and reliability properties. The parameters estimators are discussed using objective reference Bayesian analysis for both complete and censored data where the resulting marginal posterior intervals have accurate frequentist coverage. A simulation study is presented to compare the performance of the proposed estimators with the frequentist approach where it is observed a clear advantage for the Bayesian method. Finally, the proposed methodology is illustrated on three real datasets. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500202 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500202 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765201920190002 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
dc.source.none.fl_str_mv |
Anais da Academia Brasileira de Ciências v.91 n.3 2019 reponame:Anais da Academia Brasileira de Ciências (Online) instname:Academia Brasileira de Ciências (ABC) instacron:ABC |
instname_str |
Academia Brasileira de Ciências (ABC) |
instacron_str |
ABC |
institution |
ABC |
reponame_str |
Anais da Academia Brasileira de Ciências (Online) |
collection |
Anais da Academia Brasileira de Ciências (Online) |
repository.name.fl_str_mv |
Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC) |
repository.mail.fl_str_mv |
||aabc@abc.org.br |
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1754302867670302720 |