An Empirical Comparison of Some Product Estimators

Authors

  • R.K. Sahoo School of Statistics, Gangadhar Meher University, Sambalpur 768004, India
  • Ajit Kumar Sabat School of Statistics, Gangadhar Meher University, Sambalpur 768004, India
  • R.K. Nayak Khallikote Higher Secondary School, Bramhapur 760001, Ganjam, India
  • L.N. Sahoo Institute of Mathematics & Applications, Andharua, Bhubaneswar 751003, India

DOI:

https://doi.org/10.29244/ijsa.v6i2p318-335

Keywords:

auxiliary variable, prediction approach, product estimator

Abstract

In this paper, we undertake an extensive comparative study of some biased, almost unbiased and unbiased product estimators on the ground of different performance measures through Monte Carlo simulation that has not yet been initiated in the survey sampling literature. The simulation experiment is conducted using data on 20 natural populations available in the literature, and the performance indicators taken into consideration are the absolute relative bias, percentage relative efficiency, coverage rate of confidence intervals, standard deviation of the student t-statistic, and approach to symmetry (normality). This empirical study will not only facilitate to assess the overall relative performance of different competing product or product-type estimators but will also be beneficial to provide some guidelines towards further research in this direction.

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Author Biographies

R.K. Sahoo, School of Statistics, Gangadhar Meher University, Sambalpur 768004, India

School of Statistics, Gangadhar Meher University

Sambalpur 768004, India

Ajit Kumar Sabat , School of Statistics, Gangadhar Meher University, Sambalpur 768004, India

School of Statistics, Gangadhar Meher University

Sambalpur 768004, India

R.K. Nayak, Khallikote Higher Secondary School, Bramhapur 760001, Ganjam, India

Khallikote Higher Secondary School

Bramhapur 760001, Ganjam, India

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Published

31-08-2022

How to Cite

Sahoo, R., Sabat , A. K., Nayak, R., & Sahoo, L. (2022). An Empirical Comparison of Some Product Estimators. Indonesian Journal of Statistics and Its Applications, 6(2), 318–335. https://doi.org/10.29244/ijsa.v6i2p318-335

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Articles