We have also given an empirical study along with pictorial representation to examine the merit of the proposed estimator.
📌 3 Key Takeaways
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Objective & Hypothesis:In successive sampling, the use of auxiliary information for estimation of population mean on current occasion is a well explored area.
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Key Findings & Data:In the present work, the information on an auxiliary variable, which is available on both the occasions, is used along with the information on the study variable from the previous occasion and the current occa- sion.
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Conclusion & Impact:We have also given an empirical study along with pictorial representation to examine the merit of the proposed estimator.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Successive sampling · Chain type ratio estimator · Optimal replace- ment policy
Abstract
In successive sampling, the use of auxiliary information for estimation of population mean on current occasion is a well explored area. In the present work, the information on an auxiliary variable, which is available on both the occasions, is used along with the information on the study variable from the previous occasion and the current occa- sion. Consequently, chain regression-type estimator for estimating the population mean are proposed in two occasions successive sampling. The optimal replacement policy is also discussed. We have also given an empirical study along with pictorial representation to examine the merit of the proposed estimator.
TARRAY, T. A., DIXIT, S., SRİVASTAVA, N., SİNGH, H. P., SİNGH, V., SRIVASTAVA, M. K. (2022). Chain regression-type estimator using multiple auxiliary information in successive sampling. Hacettepe Journal of Mathematics and Statistics, Cilt: 44 - Sayı: 5, 1247–1256. https://ajindex.com/articles/529029