Parameter estimation for first-order superdiagonal bilinear time series: An
algorithm for maximum likelihood procedure
by
Bouzaachane Khadija, Harti Mostafa, Benghabrit Youssef.
Abstract:
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. Key Words:
First-order subdiagonal Bilinear Model, Kalman Filter, Pseudo Maximum Likelihood
Authors:
Bouzaachane Khadija, bouzaachane@netcourrier.com
Harti Mostafa, mharti@fsdmfes.ac.ma
Benghabrit Youssef, you_benghabrit@yahoo.fr
Editor:
Peiris Shelton,shelton@maths.usyd.edu.au
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