Sciweavers

Share
WCE
2007

Procedures of Parameters' estimation of AR(1) models into lineal state-space models

9 years 9 months ago
Procedures of Parameters' estimation of AR(1) models into lineal state-space models
—The objective of this paper is to study how algorithms of optimization affect the parametersestimation of Autoregressive AR(1)Models. In our research we have represented the AR(1) models in linear state space form and applied the Kalman Filters to estimate the different unknown parameters of the model. Many methods have been proposed by researchers for the estimation of the parameters in the case of the linear state space models. In our work we have emphasized on the estimation through the Maximum Likelihood (ML). Statisticians have used many algorithms to optimise the likelihood function and they have proposed many filters; publishing their results in many papers. In spite of the fact that this field is so extended, we have emphasized our study in the financial field. Two quasi-Newton algorithms: Berndt, Hall, Hall, and Hausman (BHHH) and Broyden-Fletcher-Goldfarb-Shanno (BFGS), and the Expectation-Maximization (EM) algorithm have been chosen for this study. A practical study...
Rouhia Noomene
Added 07 Nov 2010
Updated 07 Nov 2010
Type Conference
Year 2007
Where WCE
Authors Rouhia Noomene
Comments (0)
books