Efficiency of Ratio, Product, and Regression Estimators under Maximum and Minimum Values, Using Two Auxiliary Variables
Joint Authors
Khan, Mursala
al-Hossain, Abdullah Y.
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-13
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
To obtain the best estimates of the unknown population parameters have been the key theme of the statisticians.
In the present paper we have suggested some estimators which estimate the population parameters efficiently.
In short we propose a ratio, product, and regression estimators using two auxiliary variables, when there are some maximum and minimum values of the study and auxiliary variables, respectively.
The properties of the proposed strategies in terms of mean square errors (variances) are derived up to first order of approximation.
Also the performance of the proposed estimators have shown theoretically and these theoretical conditions are verified numerically by taking four real data sets under which the proposed class of estimators performed better than the other previous works.
American Psychological Association (APA)
al-Hossain, Abdullah Y.& Khan, Mursala. 2014. Efficiency of Ratio, Product, and Regression Estimators under Maximum and Minimum Values, Using Two Auxiliary Variables. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-491126
Modern Language Association (MLA)
al-Hossain, Abdullah Y.& Khan, Mursala. Efficiency of Ratio, Product, and Regression Estimators under Maximum and Minimum Values, Using Two Auxiliary Variables. Journal of Applied Mathematics No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-491126
American Medical Association (AMA)
al-Hossain, Abdullah Y.& Khan, Mursala. Efficiency of Ratio, Product, and Regression Estimators under Maximum and Minimum Values, Using Two Auxiliary Variables. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-491126
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-491126