Parameter estimation for first-order superdiagonal bilinear time series: An
algorithm for maximum likelihood procedure
Bouzaachane Khadija, Harti Mostafa, Benghabrit Youssef.
Thanks to their possible application to a wide variety of fields including
signal, demography, economics..., the bilinear time series models have acquired a great importance
in the statistical literature. This paper deals with the design of a new algorithm for estimating the parameters of a particular bilinear time series model. This iterative algorithm is based on maximum likelihood method and Kalman filter algorithm. To demonstrate the efficiency of our algorithm, series of simulations were performed.
First-order subdiagonal Bilinear Model, Kalman Filter, Pseudo Maximum Likelihood
Bouzaachane Khadija, firstname.lastname@example.org
Harti Mostafa, email@example.com
Benghabrit Youssef, firstname.lastname@example.org
READING THE ARTICLE: You can read the article in
portable document (.pdf) format (153031 bytes.)
NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.
This page has been accessed 2460 times since July 26, 2006.
Return to the Home Page.