Sequential estimation for time series regression models

✍ Scribed by Takayuki Shiohama; Masanobu Taniguchi

• Publisher: Elsevier Science
• Year: 2004
• Tongue: English
• Weight: 297 KB
• Volume: 123
• Category: Article
• ISSN: 0378-3758
• DOI: 10.1016/s0378-3758(03)00153-8

✦ Synopsis

Sequential procedures are proposed to estimate the regression parameters in a linear regression model with dependent residuals. The error process considered here is a linear process with unknown spectral density. The sequential point estimator for the regression parameters is based on the least-squares estimator and is shown to be asymptotically risk e cient under some natural conditions on the design sequence. Simulation studies are given to evaluate the asymptotic performances of the sequential procedures of the sequential estimator.