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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Detalhes bibliográficos
Autor: Mauricio Arias, José Alberto
Tipo de documento: relatório científico
Data de publicação:1993
País:España
Recursos:Universidad Complutense de Madrid (UCM)
Repositório:Docta Complutense
Idioma:inglês
OAI Identifier:oai:docta.ucm.es:20.500.14352/64200
Acesso em linha:https://hdl.handle.net/20.500.14352/64200
Access Level:Acceso aberto
Palavra-chave:Vector ARMA model
Econometría (Economía)
5302 Econometría
Descrição
Resumo: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.