The exact likelihood function for the vector ARMA model

This paper implements in Fortran 77 a new algorithm which has the same purpose as algorithm AS 242 of Shea (1989), namely to compute the exact likelihood function of a vector ARMA model. The new algorithm turns out to be faster in many relevant cases and not appreciably slower in any. In addition to...

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Detalles Bibliográficos
Autor: Mauricio Arias, José Alberto
Tipo de recurso: informe técnico
Fecha de publicación:1993
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/64200
Acceso en línea:https://hdl.handle.net/20.500.14352/64200
Access Level:acceso abierto
Palabra clave:Vector ARMA model
Econometría (Economía)
5302 Econometría
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spelling The exact likelihood function for the vector ARMA modelMauricio Arias, José AlbertoVector ARMA modelEconometría (Economía)5302 EconometríaThis paper implements in Fortran 77 a new algorithm which has the same purpose as algorithm AS 242 of Shea (1989), namely to compute the exact likelihood function of a vector ARMA model. The new algorithm turns out to be faster in many relevant cases and not appreciably slower in any. In addition to advantages offered by the algorithm of Shea (1989), including the calculation of an appropiate set of residuals, it also permits the automatic detection of noninvertible models as a byproduct. The Fortran 77 code presented here combines improved versions of the algorithms due to Ljung and Box (1979) and Hall and Nicholls (1980) with an algorithm of Kohn and Ansley (1982). The resulting procedure puts together a set of useful features which can only be found separately in other existing methods.Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)Universidad Complutense de Madrid19931993-01-0119931993-01-01technical reporthttp://purl.org/coar/resource_type/c_18ghinfo:eu-repo/semantics/reportapplication/pdfhttps://hdl.handle.net/20.500.14352/64200reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución-NoComercial-CompartirIgual 3.0 Españahttps://creativecommons.org/licenses/by-nc-sa/3.0/es/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/642002026-06-02T12:44:21Z
dc.title.none.fl_str_mv The exact likelihood function for the vector ARMA model
title The exact likelihood function for the vector ARMA model
spellingShingle The exact likelihood function for the vector ARMA model
Mauricio Arias, José Alberto
Vector ARMA model
Econometría (Economía)
5302 Econometría
title_short The exact likelihood function for the vector ARMA model
title_full The exact likelihood function for the vector ARMA model
title_fullStr The exact likelihood function for the vector ARMA model
title_full_unstemmed The exact likelihood function for the vector ARMA model
title_sort The exact likelihood function for the vector ARMA model
dc.creator.none.fl_str_mv Mauricio Arias, José Alberto
author Mauricio Arias, José Alberto
author_facet Mauricio Arias, José Alberto
author_role author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv Vector ARMA model
Econometría (Economía)
5302 Econometría
topic Vector ARMA model
Econometría (Economía)
5302 Econometría
description This paper implements in Fortran 77 a new algorithm which has the same purpose as algorithm AS 242 of Shea (1989), namely to compute the exact likelihood function of a vector ARMA model. The new algorithm turns out to be faster in many relevant cases and not appreciably slower in any. In addition to advantages offered by the algorithm of Shea (1989), including the calculation of an appropiate set of residuals, it also permits the automatic detection of noninvertible models as a byproduct. The Fortran 77 code presented here combines improved versions of the algorithms due to Ljung and Box (1979) and Hall and Nicholls (1980) with an algorithm of Kohn and Ansley (1982). The resulting procedure puts together a set of useful features which can only be found separately in other existing methods.
publishDate 1993
dc.date.none.fl_str_mv 1993
1993-01-01
1993
1993-01-01
dc.type.none.fl_str_mv technical report
http://purl.org/coar/resource_type/c_18gh
dc.type.openaire.fl_str_mv info:eu-repo/semantics/report
format report
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/64200
url https://hdl.handle.net/20.500.14352/64200
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial-CompartirIgual 3.0 España
https://creativecommons.org/licenses/by-nc-sa/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial-CompartirIgual 3.0 España
https://creativecommons.org/licenses/by-nc-sa/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
publisher.none.fl_str_mv Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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