Novel efficient estimators of finite population mean in stratified random sampling with application
Novel efficient estimators of finite population mean in stratified random sampling with application
About this item
Full title
Author / Creator
Department of Statistics, The Islamia University Bahawalpur, Punjab Pakistan , Department of Statistics, Faculty of Science, University of Tabuk Saudi Arabia , Department of Statistics University of Peshawar, Pakistan , Department of Industrial Engineering, King Saud University, Riyadh 12372, Saudi Arabia , Sher, Khazan , Ameeq, Muhammad , Hassan, Muhammad Muneeb , Alkhaleel, Basem A. , Naz, Sidra and Albalawi, Olyan
Publisher
AIMS Press
Journal title
Language
English
Formats
Publication information
Publisher
AIMS Press
Subjects
More information
Scope and Contents
Contents
Unbiased estimators are valuable when no auxiliary information is available beyond the primary study variables. However, once auxiliary information is accessible, biased estimators with smaller Mean Square Error (MSE) often outperform unbiased estimators that have large variances. We sought to develop new estimators that incorporate a single auxili...
Alternative Titles
Full title
Novel efficient estimators of finite population mean in stratified random sampling with application
Authors, Artists and Contributors
Author / Creator
Department of Statistics, Faculty of Science, University of Tabuk Saudi Arabia
Department of Statistics University of Peshawar, Pakistan
Department of Industrial Engineering, King Saud University, Riyadh 12372, Saudi Arabia
Sher, Khazan
Ameeq, Muhammad
Hassan, Muhammad Muneeb
Alkhaleel, Basem A.
Naz, Sidra
Albalawi, Olyan
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_crossref_primary_10_3934_math_2025254
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_3934_math_2025254
Other Identifiers
ISSN
2473-6988
E-ISSN
2473-6988
DOI
10.3934/math.2025254
