IMPROVED RATIO TYPE ESTIMATOR USING JACK- KNIFE METHOD OF ESTIMATION

Authors

  • Jharna Banerjie Department of Statistics, D.A.V. (P.G.) College, Dehradun, India
  • Neeraj Tiwari Department of Statistics, Kumaon University, S.S.J. Campus, Almora, India

Keywords:

Ratio estimator, coefficient of variation, unbiasedness, mean square error, Jack-Knife technique.

Abstract

In this paper, we propose to use an improved sampling strategy based on the modified ratio estimator using the population coefficient of variation and the coefficient of kurtosis of the auxiliary variable by Upadhyay and Singh (1999) for estimating the population mean (total) of the study variable in a finite population. Also the proposed sampling strategy is shown to be better in the sense of unbiased and smaller mean square error. A generalized Jack-Knife estimator is proposed and it is shown that the proposed Jack-Knife estimator is unbiased to the first order of approximation. A comparative study is made with usual sampling strategies utilizing the optimizing value of the characterizing scalar.

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References

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Published

2011-06-06

How to Cite

Banerjie, J. ., & Tiwari, N. . (2011). IMPROVED RATIO TYPE ESTIMATOR USING JACK- KNIFE METHOD OF ESTIMATION. Journal of Reliability and Statistical Studies, 4(1), 53–63. Retrieved from https://journals.riverpublishers.com/index.php/JRSS/article/view/21995

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