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Efficient Variance Estimation Strategy in Two-Occasion Successive Sampling
Abstract
Variation in nature is inevitable; it is present everywhere in our day to day life. In the present manuscript, we are introducing a new class of estimators for estimating the variation phenomenon of a finite population with the help of an additional information under two-occasion rotation sampling scheme. Properties and efficiency of this class of estimators has been illustrated and its optimum replacement strategy has been established. The comparison between the proposed class of estimators with the sample variance estimator through empirical studies, carried over a few natural population datasets, suggests the soundness and usefulness of the proposed estimator in practice.
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