An Efficient Product Estimator using Harmonic Mean

International Journal of Mathematics Trends and Technology (IJMTT)
© 2017 by IJMTT Journal
Volume-50 Number-5
Year of Publication : 2017
Authors : K. B. Panda, N. Sahoo


K. B. Panda, N. Sahoo "An Efficient Product Estimator using Harmonic Mean", International Journal of Mathematics Trends and Technology (IJMTT). V50(5):276-278 October 2017. ISSN:2231-5373. Published by Seventh Sense Research Group.

In this paper a new product estimator has been proposed by exploiting the product estimators due to Srivastava (1983), Agrawal and Jain (1989) and Panda and Sahoo (2015) . The expressions of the bias and mean square error of the proposed estimator, to the first order of approximation, are derived in general form. The new product estimator is found to perform better than its competing estimators from the standpoint of bias and mean square error both in one-phase sampling and twophase sampling under conditions which hold good in practice. The theoretical findings are supported by a numerical illustration.

1. Adewara, A.A.,Singh, Rajesh and Mukesh Kumar (2012): “Efficiency of some modified ratio and product estimators using known value of some population parameters”, International journal of applied science and technology, Vol.2, No.2, 76-79.
2. Agrawal, M.C. and Jain, N. (1989): “ A new predictive product estimator ”, Biometrika, 76(4), 822-823.
3. Basu, D. (1971): “ An essay on the logical foundations of survey sampling, Part I, Foundations of statistical inference, Ed. By V.P. Godambe and D.A. Sprott, New York 1971,203-233.
4. Maddala, G.S. (1977): “ Econometrics”, McGraw Hills Pub. Co., New York.
5. Panda, K.B. and Sahoo, N. (2015): “Study on product estimation”, International journal of multidisciplinary research review, Vol.1,Issue –10, Dec -2015. Page 165- 167.
6. Srivastava, S.K. (1983): “Predictive estimation of finite population mean using product estimator”, Metrika, 30, 93-99.
7. Sukhatme, P.V., Sukhatme, B.V., Sukhatme,S. and Asok, C.(1984): „‟Sampling theory of surveys with applications‟‟, Iowa State University press, USA.

Auxiliary variable, Product estimator, Bias and Mean squared error, Predictive estimation.