International Journal of Applied Mathematics, Computational Science and Systems Engineering
E-ISSN: 2766-9823
Volume 8, 2026
On the Applicability and Efficiency οf Calibrated Variance Estimators Utilizing Auxiliary Information Under Stratified Random Sampling
Authors: , ,
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Abstract: Estimating variance is a common practice among statisticians particularly, survey statisticians. The estimate of variance gives information about the spread within the dataset, and allows the statisticians make vital decision about the event at hand at that moment. Existing variance estimators are function of unknown constants whose applicability is not possible in real life situation. In this paper, we intend to modify some existing variance estimators using coefficient of variation and kurtosis of auxiliary variable as auxiliary information that are free of unknown constants, and are applicable in real life situation. Optimization approach (Lagrange function) was used to obtain the calibration weights of newly proposed estimators and therefore the proposed calibration variance estimators were obtained. A simulation study was used to prove the better efficiency (minimum mean square error) of these proposed estimators.
Pages: 126-133
DOI: 10.37394/232026.2026.8.12