Journal of Jilin University Science Edition
Previous Articles Next Articles
ZHOU Ling, HE Daojiang
Received:
Online:
Published:
Contact:
Abstract:
To combat autocorrelation in errors and multicollinearity among the regressors in linear regression model, we proposed a new estimator by combining the principal components regression (PCR) estimator and the s-K estimator. Then necessary and sufficient conditions for the superiority of the new estimator over the GLS, the PCR, the r-k and the s-K estimators were derived by the mean squared error matrix criterion. Finally, a Monte Carlo simulation study was carried out to investigate the performance of the proposed estimator.
Key words: autocorrelation, multicollinearity, principal components regression estimator, s-K estimator, mean squared error matrix
CLC Number:
ZHOU Ling, HE Daojiang. Principal Components s-K Class Estimator inthe Linear Model with Correlated Errors[J].Journal of Jilin University Science Edition, 2015, 53(03): 444-450.
0 / / Recommend
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
URL: http://xuebao.jlu.edu.cn/lxb/EN/
http://xuebao.jlu.edu.cn/lxb/EN/Y2015/V53/I03/444
Cited