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Exponential Ratio-Cum-Exponential Dual to Ratio Estimator in Double Sampling

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Forging Connections between Computational Mathematics and Computational Geometry

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 124))

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Abstract

A class of exponential ratio-cum-exponential dual to ratio estimators for estimating a finite population mean in double sampling scheme is proposed. The expressions for bias and mean squared error (MSE) of the proposed estimator have been derived for two different cases. An asymptotic expression for MSE is obtained. Empirical studies are carried out to illustrate the performance of the constructed estimator over other estimators.

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References

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Author information

Authors and Affiliations

  1. Department of Statistics, North Lakhimpur College (Autonomous), North Lakhimpur, Assam, 787001, India

    Diganta Kalita

  2. Department of Mathematics, North Eastern Regional Institute of Science and Technology, Nirjuli, Itanagar, 791109, India

    B. K. Singh

  3. Department of Mathematics, National Institute of Technology Nagaland, Nagaland, 797103, India

    Sanjib Choudhury

Authors
  1. Diganta Kalita
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  2. B. K. Singh
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  3. Sanjib Choudhury
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Corresponding author

Correspondence to Diganta Kalita .

Editor information

Editors and Affiliations

  1. Department of Mathematical Sciences, The University of Liverpool, Liverpool, UK

    Ke Chen

  2. Global Science and Technology Forum, Singapore, Singapore

    Anton Ravindran (Managing Editor, President) (Managing Editor, President)

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Kalita, D., Singh, B.K., Choudhury, S. (2016). Exponential Ratio-Cum-Exponential Dual to Ratio Estimator in Double Sampling. In: Chen, K., Ravindran, A. (eds) Forging Connections between Computational Mathematics and Computational Geometry. Springer Proceedings in Mathematics & Statistics, vol 124. Springer, Cham. https://doi.org/10.5176/2251-1911_CMCGS14.05_18

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