Model for multiple imputation to estimate daily rainfall data and filling of faults.
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1083153 http://dx.doi.org/10.1590/0102-7786324006 |
Resumo: | Modeling by multiple enchained imputation is an area of growing importance. However, its models and methods are frequently developed for specific applications. In this study the model for multiple imputation was used to estimate daily rainfall data. Daily precipitation records from several meteorological stations were used, obtained from system AGRITEMPO for two homogenous climatic zones. The precipitation values obtained for two dates (Jan. 20th 2005 and May 2nd 2005) using the multiple imputation model were compared with geo-statistics techniques ordinary Kriging and Co-kriging with the altitude as an auxiliary variable. The multiple imputation model was 16% better for the first zone and over 23% for the second one, compared to the rainfall estimation obtained by geo-statistical techniques. The model proved to be a versatile technique, presenting coherent results with the conditions of different zones and times. |
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Model for multiple imputation to estimate daily rainfall data and filling of faults.GeoestatísticaSistema AgritempoPrecipitaçãoModelagem por imputação múltiplaModel by multiple imputationPrecipitationOrdinary krigingOrdinary Co-krigingHomogeneous zonesMissing dataStatistical inferenceMeteorological dataGeostatisticsModeling by multiple enchained imputation is an area of growing importance. However, its models and methods are frequently developed for specific applications. In this study the model for multiple imputation was used to estimate daily rainfall data. Daily precipitation records from several meteorological stations were used, obtained from system AGRITEMPO for two homogenous climatic zones. The precipitation values obtained for two dates (Jan. 20th 2005 and May 2nd 2005) using the multiple imputation model were compared with geo-statistics techniques ordinary Kriging and Co-kriging with the altitude as an auxiliary variable. The multiple imputation model was 16% better for the first zone and over 23% for the second one, compared to the rainfall estimation obtained by geo-statistical techniques. The model proved to be a versatile technique, presenting coherent results with the conditions of different zones and times.Na publicação: José Eduardo Boffinho Almeida Monteiro.JOSE RUY PORTO DE CARVALHO, CNPTIA; JOSE EDUARDO B DE ALMEIDA MONTEIRO, CNPTIA; ALAN MASSARU NAKAI, CNPTIA; EDUARDO DELGADO ASSAD, CNPTIA.CARVALHO, J. R. P. deMONTEIRO, J. E. B. de A.NAKAI, A. M.ASSAD, E. D.2017-12-21T23:24:37Z2017-12-21T23:24:37Z2017-12-2120172017-12-21T23:24:37Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleRevista Brasileira de Meteorologia, São Paulo, v. 32, n. 4, 575-583, Oct./Dec. 2017.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1083153http://dx.doi.org/10.1590/0102-7786324006enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-12-21T23:24:44Zoai:www.alice.cnptia.embrapa.br:doc/1083153Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-12-21T23:24:44falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-12-21T23:24:44Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Model for multiple imputation to estimate daily rainfall data and filling of faults. |
title |
Model for multiple imputation to estimate daily rainfall data and filling of faults. |
spellingShingle |
Model for multiple imputation to estimate daily rainfall data and filling of faults. CARVALHO, J. R. P. de Geoestatística Sistema Agritempo Precipitação Modelagem por imputação múltipla Model by multiple imputation Precipitation Ordinary kriging Ordinary Co-kriging Homogeneous zones Missing data Statistical inference Meteorological data Geostatistics |
title_short |
Model for multiple imputation to estimate daily rainfall data and filling of faults. |
title_full |
Model for multiple imputation to estimate daily rainfall data and filling of faults. |
title_fullStr |
Model for multiple imputation to estimate daily rainfall data and filling of faults. |
title_full_unstemmed |
Model for multiple imputation to estimate daily rainfall data and filling of faults. |
title_sort |
Model for multiple imputation to estimate daily rainfall data and filling of faults. |
author |
CARVALHO, J. R. P. de |
author_facet |
CARVALHO, J. R. P. de MONTEIRO, J. E. B. de A. NAKAI, A. M. ASSAD, E. D. |
author_role |
author |
author2 |
MONTEIRO, J. E. B. de A. NAKAI, A. M. ASSAD, E. D. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
JOSE RUY PORTO DE CARVALHO, CNPTIA; JOSE EDUARDO B DE ALMEIDA MONTEIRO, CNPTIA; ALAN MASSARU NAKAI, CNPTIA; EDUARDO DELGADO ASSAD, CNPTIA. |
dc.contributor.author.fl_str_mv |
CARVALHO, J. R. P. de MONTEIRO, J. E. B. de A. NAKAI, A. M. ASSAD, E. D. |
dc.subject.por.fl_str_mv |
Geoestatística Sistema Agritempo Precipitação Modelagem por imputação múltipla Model by multiple imputation Precipitation Ordinary kriging Ordinary Co-kriging Homogeneous zones Missing data Statistical inference Meteorological data Geostatistics |
topic |
Geoestatística Sistema Agritempo Precipitação Modelagem por imputação múltipla Model by multiple imputation Precipitation Ordinary kriging Ordinary Co-kriging Homogeneous zones Missing data Statistical inference Meteorological data Geostatistics |
description |
Modeling by multiple enchained imputation is an area of growing importance. However, its models and methods are frequently developed for specific applications. In this study the model for multiple imputation was used to estimate daily rainfall data. Daily precipitation records from several meteorological stations were used, obtained from system AGRITEMPO for two homogenous climatic zones. The precipitation values obtained for two dates (Jan. 20th 2005 and May 2nd 2005) using the multiple imputation model were compared with geo-statistics techniques ordinary Kriging and Co-kriging with the altitude as an auxiliary variable. The multiple imputation model was 16% better for the first zone and over 23% for the second one, compared to the rainfall estimation obtained by geo-statistical techniques. The model proved to be a versatile technique, presenting coherent results with the conditions of different zones and times. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-12-21T23:24:37Z 2017-12-21T23:24:37Z 2017-12-21 2017 2017-12-21T23:24:37Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Revista Brasileira de Meteorologia, São Paulo, v. 32, n. 4, 575-583, Oct./Dec. 2017. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1083153 http://dx.doi.org/10.1590/0102-7786324006 |
identifier_str_mv |
Revista Brasileira de Meteorologia, São Paulo, v. 32, n. 4, 575-583, Oct./Dec. 2017. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1083153 http://dx.doi.org/10.1590/0102-7786324006 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
_version_ |
1794503446698655744 |