Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods
Autor(a) principal: | |
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Data de Publicação: | 1999 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/205072 |
Resumo: | Recently, the study of time series has been focused on time series having the long memory property, that is, series in which the dependence between distant observations is not negligible. One model that shows properties of long memory is the ARF IM A(p, d, q) when the degree of differencing d is in the interval (0 .0 ,0.5), range where the process is stationary. In this work, we analyze the estimation of the degree d* in ARFIMA(O,d*,O) processes when d* > 0.5, that is, when the processes are nonstationary, but still have the property of long memory. We present a study, through simulations, for the estimators of d* with different semiparametric and parametric methods for nonstationary processes when d* belongs to the intervals (0.5, 1.0) and (1.0,1.5). |
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Pasini, Bárbara Patricia OlbermannLopes, Silvia Regina CostaReisen, Valderio Anselmo2020-01-30T04:09:15Z1999http://hdl.handle.net/10183/205072000289599Recently, the study of time series has been focused on time series having the long memory property, that is, series in which the dependence between distant observations is not negligible. One model that shows properties of long memory is the ARF IM A(p, d, q) when the degree of differencing d is in the interval (0 .0 ,0.5), range where the process is stationary. In this work, we analyze the estimation of the degree d* in ARFIMA(O,d*,O) processes when d* > 0.5, that is, when the processes are nonstationary, but still have the property of long memory. We present a study, through simulations, for the estimators of d* with different semiparametric and parametric methods for nonstationary processes when d* belongs to the intervals (0.5, 1.0) and (1.0,1.5).application/pdfengCadernos de matemática e estatística. Série A, Trabalho de pesquisa. Porto Alegre. N. 53 (nov. 1999), p. 1-17.Estatistica : EstimacaoSéries temporais : Processos ARFIMA : Parâmetro fracionário : EstimadoresEstimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methodsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT000289599.pdf.txt000289599.pdf.txtExtracted Texttext/plain0http://www.lume.ufrgs.br/bitstream/10183/205072/2/000289599.pdf.txtd41d8cd98f00b204e9800998ecf8427eMD52ORIGINAL000289599.pdfTexto completo (inglês)application/pdf8114619http://www.lume.ufrgs.br/bitstream/10183/205072/1/000289599.pdffb4165efc80aefd5bd912b99a07b7e9aMD5110183/2050722021-06-26 04:38:28.71361oai:www.lume.ufrgs.br:10183/205072Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2021-06-26T07:38:28Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods |
title |
Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods |
spellingShingle |
Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods Pasini, Bárbara Patricia Olbermann Estatistica : Estimacao Séries temporais : Processos ARFIMA : Parâmetro fracionário : Estimadores |
title_short |
Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods |
title_full |
Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods |
title_fullStr |
Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods |
title_full_unstemmed |
Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods |
title_sort |
Estimation of the long memory parameter in nonstationary time series using semi-parametric and parametric methods |
author |
Pasini, Bárbara Patricia Olbermann |
author_facet |
Pasini, Bárbara Patricia Olbermann Lopes, Silvia Regina Costa Reisen, Valderio Anselmo |
author_role |
author |
author2 |
Lopes, Silvia Regina Costa Reisen, Valderio Anselmo |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Pasini, Bárbara Patricia Olbermann Lopes, Silvia Regina Costa Reisen, Valderio Anselmo |
dc.subject.por.fl_str_mv |
Estatistica : Estimacao Séries temporais : Processos ARFIMA : Parâmetro fracionário : Estimadores |
topic |
Estatistica : Estimacao Séries temporais : Processos ARFIMA : Parâmetro fracionário : Estimadores |
description |
Recently, the study of time series has been focused on time series having the long memory property, that is, series in which the dependence between distant observations is not negligible. One model that shows properties of long memory is the ARF IM A(p, d, q) when the degree of differencing d is in the interval (0 .0 ,0.5), range where the process is stationary. In this work, we analyze the estimation of the degree d* in ARFIMA(O,d*,O) processes when d* > 0.5, that is, when the processes are nonstationary, but still have the property of long memory. We present a study, through simulations, for the estimators of d* with different semiparametric and parametric methods for nonstationary processes when d* belongs to the intervals (0.5, 1.0) and (1.0,1.5). |
publishDate |
1999 |
dc.date.issued.fl_str_mv |
1999 |
dc.date.accessioned.fl_str_mv |
2020-01-30T04:09:15Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/other |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/205072 |
dc.identifier.nrb.pt_BR.fl_str_mv |
000289599 |
url |
http://hdl.handle.net/10183/205072 |
identifier_str_mv |
000289599 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Cadernos de matemática e estatística. Série A, Trabalho de pesquisa. Porto Alegre. N. 53 (nov. 1999), p. 1-17. |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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