A Generalized Class of Exponential Type Estimators for Population Mean under Systematic Sampling Using Two Auxiliary Variables
Author
Source
Journal of Probability and Statistics
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-17
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
We have proposed a generalized class of exponential type estimators for population mean under the framework of systematic sampling using the knowledge of two auxiliary variables.
The expressions for the mean square error of the proposed class of estimators have been corrected up to first order of approximation.
Comparisons of the efficiency of the proposed class of estimators under the optimal conditions with the other existing estimators have been presented through a real secondary data.
The statistical study provides strong evidence that the proposed class of estimators in survey estimation procedure results in substantial efficiency improvements over the other existing estimation approaches.
American Psychological Association (APA)
Khan, Mursala. 2016. A Generalized Class of Exponential Type Estimators for Population Mean under Systematic Sampling Using Two Auxiliary Variables. Journal of Probability and Statistics،Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1110255
Modern Language Association (MLA)
Khan, Mursala. A Generalized Class of Exponential Type Estimators for Population Mean under Systematic Sampling Using Two Auxiliary Variables. Journal of Probability and Statistics No. 2016 (2016), pp.1-6.
https://search.emarefa.net/detail/BIM-1110255
American Medical Association (AMA)
Khan, Mursala. A Generalized Class of Exponential Type Estimators for Population Mean under Systematic Sampling Using Two Auxiliary Variables. Journal of Probability and Statistics. 2016. Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1110255
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1110255