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Chain-type ratio estimator in successive sampling using multi-auxiliary information

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  • Manoj Kumar Srivastava
  • Namita Srivastava

Abstract

The present work is an attempt to make use of several auxiliary variables at both the occasions for improving the precision of estimates at the current occasion on two occasions of successive sampling. Chain-type ratio estimator has been proposed for estimating the population mean at current occasion in two occasions rotation (successive) sampling. Theoretical properties of the proposed estimator have been investigated. The proposed estimator has been compared with simple mean estimator when there is no matching and with the ratio estimator in successive sampling when information is available on one auxiliary variable on both the occasions. Optimum replacement strategy has also been discussed. Theoretical results have been justified through empirical investigation.

Suggested Citation

  • Manoj Kumar Srivastava & Namita Srivastava, 2016. "Chain-type ratio estimator in successive sampling using multi-auxiliary information," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(16), pages 4798-4811, August.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:16:p:4798-4811
    DOI: 10.1080/03610926.2014.930907
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