Convergence to Normality of the Asymptotic Quasi-Score Function on a Linear Model

✍ Scribed by Sifa Mvoi; Yan-Xia Lin

• Publisher: John Wiley and Sons
• Year: 2000
• Tongue: English
• Weight: 180 KB
• Volume: 42
• Category: Article
• ISSN: 0323-3847
• DOI: 10.1002/(sici)1521-4036(200005)42:2<239::aid-bimj239>3.0.co;2-1

✦ Synopsis

The asymptotic quasi-likelihood method is considered for the model y t f t q M t ; t 0; 1; . . . ; T where f t q is a linear predictable process of the parameter of interest q, M t is a martingale difference, and the nature of EM 2 t j p tÀ1 is unknown. This paper is concerned with the limiting distribution of the asymptotic quasi-score function of such a model. Confidence intervals and hypothesis testing of q is derived from the limiting distribution. Comparison is made between the estimates obtained through this method and those obtained through the least squares method.