Robust ratio-type estimators in simple random sampling


Oral E., KADILAR C.

JOURNAL OF THE KOREAN STATISTICAL SOCIETY, vol.40, no.4, pp.457-467, 2011 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 40 Issue: 4
  • Publication Date: 2011
  • Doi Number: 10.1016/j.jkss.2011.04.001
  • Title of Journal : JOURNAL OF THE KOREAN STATISTICAL SOCIETY
  • Page Numbers: pp.457-467

Abstract

In sampling theory, ratio-type estimators are extensively used to estimate the population mean when the correlation between study and auxiliary variables is positively high. In this study, we incorporate robust modified maximum likelihood estimators (MMLEs) into Kadilar-Cingi estimators and provide their properties theoretically. We support the theoretical results with simulations under numerous super-population models, and study the robustness properties of these modified estimators. We show that utilization of MMLEs in estimating the mean of a finite population leads to robust estimates, which is very advantageous when we have non-normality or other common data anomalies such as outliers. (C) 2011 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.