A dual auxiliary variable approach to finite population variance estimation

Articles in Press

Document Type : Original Article

Authors
Abid Hussain
Rabbia Mukhtar
Muhammad Asim Masood
Nasir Ali
Department of Statistics, PMAS-Arid Agriculture University, Rawalpindi, Pakistan.
10.22034/jirss.2026.2064841.1120
Abstract
This study proposes a novel estimator for the finite population variance under simple random sampling. The estimator utilizes dual auxiliary information by incorporating the empirical cumulative distribution function (ECDF) of an auxiliary variable. The ECDF, which represents the stochastic process over the unit interval [0,1], is employed to enhance the estimation precision. The performance of the proposed estimator is evaluated through a comprehensive analysis. First, the bias and mean squared error (MSE) of the estimator are derived analytically. Second, a simulation study is conducted to investigate the estimator's behavior under various parametric settings. Finally, an empirical comparison is made with several well-established estimators using five real-world datasets. The results consistently demonstrate the superiority of the proposed estimator in terms of both bias and MSE, suggesting its practical utility.
Keywords
Auxiliary information
simple random sampling
mean squared error
empirical distribution function
simulation
Subjects
Journal of the Iranian Statistical Society

Articles in Press, Accepted Manuscript
Available Online from 24 May 2026

  • Receive Date 05 July 2025
  • Revise Date 18 May 2026
  • Accept Date 19 May 2026