標題: Trimmed least squares estimator as best trimmed linear conditional estimator for linear regression model
作者: Chen, LA
Thompson, P
統計學研究所
Institute of Statistics
關鍵字: instrumental variables estimator;linear conditional estimator;linear regression;regression quantile;trimmed least squares estimator
公開日期: 1998
摘要: A class of trimmed linear conditional estimators based on regression quantiles for the linear regression model is introduced. This class serves as a robust analogue of non-robust linear unbiased estimators. Asymptotic analysis then shows that the trimmed least squares estimator based on regression quantiles (Koenker and Bassett (1978)) is the best in this estimator class in terms of asymptotic covariance matrices. The class of trimmed linear conditional estimators contains the Mallows-type bounded influence trimmed means (see De Jongh et al (1988)) and trimmed instrumental variables estimators. A large sample methodology based on trimmed instrumental variables estimator for confidence ellipsoids and hypothesis testing is also provided.
URI: http://hdl.handle.net/11536/111
ISSN: 0361-0926
期刊: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Volume: 27
Issue: 7
起始頁: 1835
結束頁: 1849
顯示於類別:期刊論文


文件中的檔案:

  1. 000074669900014.pdf