An improved class of robust ratio estimators by using the minimum covariance determinant estimation

Bulut H., ZAMAN T.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, vol.51, no.5, pp.2457-2463, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 51 Issue: 5
  • Publication Date: 2022
  • Doi Number: 10.1080/03610918.2019.1697818
  • Journal Name: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Computer & Applied Sciences, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.2457-2463
  • Keywords: Ratio-type estimators, MCD estimation, Robust regression coefficients, MSE, Efficiency
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

In this article, ratio estimators for the population mean have suggested using the robust covariance estimation under the simple random scheme. Zaman and Bulut have developed a class of ratio-type estimators for the mean estimation by utilizing robust regression coefficients. In this paper, we extend the estimators presented in Zaman and Bulut by using minimum covariance determinant (MCD) robust covariance estimation. The mean square error (MSE) equation for the new estimators is obtained. These theoretical results are supported with the aid of numerical example and simulation based on dataset that include outliers.