A class of exponential chain ratio-product type estimators with two auxiliary variables under double sampling scheme

Authors

  • B. K. Singh North Eastern Regional Institute of Science and Technology
  • Sanjib Choudhury National Institute of Technology Nagaland
  • Diganta Kalita North Lakhimpur College (Autonomus)

DOI:

https://doi.org/10.1285/i20705948v6n2p166

Keywords:

Auxiliary information, Exponential chain ratio-product type estimator in double sampling, Mean square error, Efficiency.

Abstract

In this paper an exponential chain ratio-product-type estimators in double sampling has been developed using information on two supplementary characters for estimating the finite population mean. The optimum property of the suggested strategy has been studied. Comparisons of the efficiency of the proposed estimator under the optimality condition with other estimators have been presented through empirical investigations.

References

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Murthy, M. N. (1967). Sampling theory and methods. Calcutta, India: Statistical Publishing Soc.

Singh, B. K. & Choudhury, S. (2012) Exponential chain ratio and product type estimators for finite population mean under double sampling scheme, Global Journal of Science Frontier Research, 12(6), 13-24.

Singh, H. P. & Vishwakarma, G. K. (2007). Modified exponential ratio and product estimators for finite population mean in double sampling. Austrian Journal of Statistics, 36(3), 217-225.

Singh, V. K., Singh, G. N. & Shukla, D. (1994). A class of chain ratio type estimators with two auxiliary variables under double sampling scheme. Sankhyā, 56 (2), 209-221.

Srivnstava, Rani S., Srivastava, S. P., & Khare, B. B. (1989). Chain ratio type estimator for ratio of two population means using auxiliary characters. Communications in Statistics –Theory and Methods, 18(10), 3917-3926.

Sukhatme, B. V., & Chand, L. (1977). Multivariate ratio-type estimators. Proceedings of American Statistical Association, Social Statistics Section, 927–931.

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Published

14-10-2013

Issue

Vol. 6 No. 2 (2013): Electronic Journal of Applied Statistical Analysis

Section

Original Paper

License

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