International Journal of Mathematics Trends and Technology
Volume 56 | Number 6 | Year 2018 | Article Id. IJMTT-V56P558 | DOI : https://doi.org/10.14445/22315373/IJMTT-V56P558
−In this paper, extending the work of hierarchic estimation proposed by Agrawal and Sthapit(1997), we define a multivariate product estimator using harmonic means of multi-auxiliary variables which conforms to predictive character. Furthermore, it has been shown that the proposed multivariate product estimator of order k, when k is determined optimally, fares better than its competitors both in terms of bias and mean square error under some practical conditions. Empirical investigations in support of the theoretical findings have been carried out.
1. Agrawal, M.C. & Sthapit, A. B. (1997): Hierarchic predictive ratio-based & product-based estimators and their efficiencies. Journal of Applied Statistics, VoI. 24, No-1, 97-104.
2. Agrawal, M.C. & Panda, K.B.(1993): Multivariate product estimators, Jour. Ind. Soc. Ag. Statistics, 45(3).359-371.
3. Basu, D.(1971): An essay on the logical foundations of statistical inference, Part I, Foundations of Statistical Inference, Ed. By V.P. Godambe and D.A. Sportt, New York, 203-233.
4. Panda, K.B. and Sahoo, N.(2015): Systems of exponential ratio-based and exponential product-based estimators with their efficiency. ISOR Journal of Mathematics, Volume 11, Issue 3 Ver.I(May-June),PP 73-77.
5. Weisberg, S. (1980): Applied linear regression analysis, John Wiley & Sons, Inc., New York.
K.B. Panda, P. Das, "Efficient Hierarchic Predictive Multivariate Product Estimator Based On Harmonic Mean," International Journal of Mathematics Trends and Technology (IJMTT), vol. 56, no. 6, pp. 437-442, 2018. Crossref, https://doi.org/10.14445/22315373/IJMTT-V56P558
PDF 
Abstract 
Keywords 
References 
Citation