Efficient use of auxiliary information in the estimation of population variance in sample surveys
Abstract
The present paper we proposed some new estimators to estimate the population variance of study variable using the auxiliary information in simple random sampling without replacement scheme. The expressions for its bias and mean square errors have been obtained. To show the theoretical results we compare our proposed estimators with natural variance and traditional ratio estimator suggested by Isaki (1983) [1]. Empirical studies are carried out to examine the performances of the proposed estimators and consequently the suitable recommendations are made.
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- Generalized multi-component estimation strategy for finite population variance under double sampling
Pranjal Kaser, Dharmendra Kumar Gangeshwer · International Journal of Statistics and Applied Mathematics · 2026
This paper presents a feasible generalized multi-component estimator for variance which for finite population of a study variable under two-phase (double) sampling. The existing estimator’s formulation combined ratio, difference and exponential adjustments but used the unknown auxiliary population variance inside the difference component. In this paper the proposed formulation replaces that quantity with the first-phase auxiliary sample variance, thereby making the estimator operational under the stated design. A first-phase simple random sample without replacement of size n′ is followed by a
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