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Iterative Weighted Semiparametric Least Squares Estimation in Repeated Measurement Partially Linear Regression Models
- Source :
- Acta Mathematicae Applicatae Sinica, English Series. 21:177-192
- Publication Year :
- 2005
- Publisher :
- Springer Science and Business Media LLC, 2005.
-
Abstract
- Consider a repeated measurement partially linear regression model with an unknown vector parameter β 1, an unknown function g(·), and unknown heteroscedastic error variances. In order to improve the semiparametric generalized least squares estimator (SGLSE) of β, we propose an iterative weighted semiparametric least squares estimator (IWSLSE) and show that it improves upon the SGLSE in terms of asymptotic covariance matrix. An adaptive procedure is given to determine the number of iterations. We also show that when the number of replicates is less than or equal to two, the IWSLSE can not improve upon the SGLSE. These results are generalizations of those in [2] to the case of semiparametric regressions.
Details
- ISSN :
- 16183932 and 01689673
- Volume :
- 21
- Database :
- OpenAIRE
- Journal :
- Acta Mathematicae Applicatae Sinica, English Series
- Accession number :
- edsair.doi...........834f72f8a0ac95d736ea806cf20458cb