On Efficient Variance Estimation for Normal Populations By Winston A. Richards, Department of Mathematics and Statistics; The Pennsylvania State University, Harrisburg, USA.
by Ashok Sahai, Robin Antoine, Kimberly Wright, and
M. Raghunadh Acharya.
This paper addresses the issue of finding an efficient estimator of the normal populations variance using the sample estimate of the population coefficient of variation. The proposed estimator is arrived at by using the well-known Searls (1964)’ perspective for the MMSE estimation of the normal population mean. Recently, Searls & Intarapanich (1990) found the MMSE of the normal population variance. We have presented the relative efficiency of our estimator with respect to usual unbiased estimator S2 vis-à-vis that of the Searls & Intarapanich (1990)’s estimator by means of an empirical simulation study.
Empirical simulation study, MMSE, Relative Efficiency, Variance estimation
Ashok Sahai, email@example.com
Winston A. Richards, firstname.lastname@example.org
Robin Antoine, email@example.com
Kimberly Wright, firstname.lastname@example.org
Raghunadh, M. Acharya, email@example.com
Ahmed H. Youssef, firstname.lastname@example.org
READING THE ARTICLE: You can read the article in
portable document (.pdf) format (246363 bytes.)
NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.
This page has been accessed 4742 times since NOVEMBER 25, 2009.
Return to the Home Page.