RT Report
T1 Fast estimation methods for time series models in state-space form
A1 García Hiernaux, Alfredo Alejandro
A1 Casals Carro, José
A1 Jerez Méndez, Miguel
AB 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.
PB Instituto Complutense de Análisis Económico. Universidad Complutense de Madrid
YR 2005
FD 2005
LK https://hdl.handle.net/20.500.14352/56624
UL https://hdl.handle.net/20.500.14352/56624
LA eng
DS Docta Complutense
RD 21 dic 2025