|
Título:
|
Fast estimation methods for time series models in state-space form
|
|
Autores:
|
Hiernaux, Alfredo G. ;
Casals Carro, José ;
Jerez Méndez, Miguel
|
|
Tipo de documento:
|
texto impreso
|
|
Editorial:
|
Instituto Complutense de Análisis Económico. Universidad Complutense de Madrid, 2005
|
|
Dimensiones:
|
application/pdf
|
|
Nota general:
|
info:eu-repo/semantics/openAccess
|
|
Idiomas:
|
|
|
Palabras clave:
|
Estado = Publicado
,
Materia = Ciencias Sociales: Economía: Econometría
,
Tipo = Documento de trabajo o Informe técnico
|
|
Resumen:
|
We propose two fast, stable and consistent methods to estimate time series models expressed in their equivalent state-space form. They are useful both, to obtain adequate initial conditions for a maximum-likelihood iteration,
or to provide final estimates when maximum-likelihood is considered inadequate or costly. The state-space foundation of these procedures implies that they can estimate any linear fixed-coefficients model, such as ARIMA, VARMAX or structural time series models. The computational and finitesample performance of both methods is very good, as a simulation exercise shows.
|
|
En línea:
|
https://eprints.ucm.es/id/eprint/7881/1/0504.pdf
|
