Chain Ratio Type Exponential Estimator for Finite Population Mean in Double Sampling

Authors

  • Ranjana Janbandhu School of Studies in Statistics, Vikram University, Ujjain (M.P.), India
  • Neha Garg School of Sciences, Indira Gandhi National Open University, New Delhi, India
  • Rajesh Tailor School of Studies in Statistics, Vikram University, Ujjain (M.P.), India

Keywords:

Bias, double sampling, chain ratio type exponential estimator, finite population mean, mean squared error

Abstract

This paper discusses the problem of estimation of finite population mean resulting in a newly developed chain ratio type exponential estimator for finite population mean in double sampling. The developed estimator is the extension of Chand (1975) chain ratio estimator using exponential strategy adopted by Bahl and Tuteja (1991). Expressions for the bias and mean squared error of the developed estimator have been obtained up to the first degree of approximation. Properties of the developed estimator haven been examined, and the developed estimator has been compared theoretically as well as empirically using simulation study in R software with usual unbiased estimator, classical ratio estimator in double sampling, Singh and Vishwakarma (2007) ratio-type exponential estimator, Chain ratio estimator given by Chand (1975) and Singh and Upadhyaya (1995) chain ratio estimator. A simulation study has been carried out on real as well as artificial datasets generated from Chi-square and normal probability distributions.

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Published

2023-06-28

How to Cite

Janbandhu, R. ., Garg, N. ., & Tailor, R. . (2023). Chain Ratio Type Exponential Estimator for Finite Population Mean in Double Sampling. Thailand Statistician, 21(3), 675–690. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/250073

Issue

Vol. 21 No. 3 (2023): July

Section

Articles

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