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The aim is to develop a generalized estimator for population variance using auxiliary information to improve estimation accuracy.

January 25, 2026MathematicsOpen Access

Computation of Population Variance Estimation in Simple Random Sampling Structures by Developing Generalized Estimator

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The aim is to develop a generalized estimator for population variance using auxiliary information to improve estimation accuracy.
Developed a generalized class of estimators for population variance using auxiliary variables.
Analyzed bias and mean squared error in relation to first-order approximation.
Compared proposed estimators with classical variance estimators using real-life data and simulations.
Evaluated estimator performance under varying population conditions and sample sizes.
The proposed estimators show lower mean squared error compared to traditional methods.
Higher relative efficiency was achieved when there's high correlation between auxiliary and study variables.
Estimation techniques proved robust across different sample sizes and population structures.

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Proposed generalized estimators improve population variance estimation in surveys, indicating enhanced precision and efficiency.

Djebar et al. (2026) studied this question.

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