COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, vol.49, no.14, pp.3407-3420, 2020 (SCI-Expanded)
Article / Article
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
Regression-type estimators, robust regression methods, robust covariance matrices, auxiliary information, relative efficiency, stratified random sampling
Ondokuz Mayıs University Affiliated:
This article proposes new regression-type estimators by considering Tukey-M, Hampel M, Huber MM, LTS, LMS and LAD robust methods and MCD and MVE robust covariance matrices in stratified sampling. Theoretically, we obtain the mean square error (MSE) for these estimators. We compare the efficiencies based on MSE equations, between the proposed estimators and the traditional combined and separate regression estimators. As a result of these comparisons, we observed that our proposed estimators give more efficient results than traditional approaches. And, these theoretical results are supported with the aid of numerical examples and simulation based on data sets that include outliers.