Alternative Ratio-Product Type Estimator in Simple Random Sampling
Keywords:Ratio estimator, product estimator, bias, mean square error, efficiency, auxiliary variables, single-phase sampling
Communication in Physical Sciences 2020, 5(4): 418-426
Received 05 March 2020/Accepted 15 June 2020
In this paper, we proposed a new alternative ratio-product estimator in simple random sampling without replacement by using information on an auxiliary variable. The proposed estimator is a mixture of some of the commonly known estimators. We have derived the minimum mean square errors up to the first order of approximation. Theoretically, we compare the mean square error (MSE) equation of the proposed estimator with the mean square error (MSE) equations of the existing estimators in literature. Numerical examples with four real data sets shows that the proposed estimator is more efficient than the existing other estimators considered. Therefore, the findings of this research are important in identifying alternative ratio-product exponential estimator, its properties, as well as relevant empirical applications.
Bahl, S. & Tuteja, R.K., (1991). Ratio and product exponential estimators, Journal of Information and Optimization Sciences, 12, 1, pp. 159-164.
Cochran, W. G. (1940). The estimation of the yields of the cereal experiments by sampling for the ratio of grain to total produce’, The Journal of Agricultural Science, 30, pp. 262–275.
Cochran, W. G. (1977). Sampling techniques. New York, NY: John Wiley and Sons.
Grover, L.K. & Kaur, P. (2011). An improved estimator of the finite population mean in simple random sampling. Model Assisted Statistics and Applications 6, 1, pp. 47-55.
Grover, L.K. & Kaur, P. (2011). An improved exponential estimator of finite population mean in simple random sampling using an auxiliary information. Applied mathematics and Computation, 218, pp. 3093-3099.
Kadilar, C., Cingi, H, (2006). An improvement in estimating the population mean by using the correlation coefficient. Hacettepe Journal of Mathematics and Statistics, 35, 1, pp. 103–109.
Muhammad, H., Naqvi, H., & Muhammad, Q. (2009). A modified Regression-type estimator in survey sampling. Applied Sciences Journal, 7, 12, pp. 1559-1561.
Murthy, M. N. (1964). Product method of estimation. The Indian Journal of Statistic A, 26, pp. 69-74
Murthy, M. N. (1967). Sampling Theory and Methods. Calcutta, India: Statistical Publishing Society.
Perri, P. F. (2005). Combining two Auxiliary Variables in Ratio-cum-product type Estimators. Proceedings of Italian Statistical Society. Intermediate meeting on Statistics and Environment, Messina, 21-23 September, 2005, 193-196.
Rao, T. J. (1991). On certain methods of improving ratio and regression estimator. Communication in statistics - Theory and Methods, 20, 10, pp. 3325-3340.
Robson, D. S. (1957). Applications of multivariate polykays to the theory of unbiased ratio-type estimation. Journal of American Statistical Association, 52, 282, pp. 491-508.
Singh, B. K., & Choudhury, S. (2012). Dual to product estimator for estimating population mean in double sampling. International Journal of Statistics and Systems, 7, 1, pp.31–9.
Solanki, R. S., Singh, H. P. & Rathour, A. (2012). An alternative estimator for estimating the finite population mean using auxiliary information in sample surveys. ISRN Probability and Statistics, 1-14.
Subramani, J. (2013). Generalized modified ratio estimator for estimation of finite population mean. Journal of Modern Applied Statistical Method, 12, 2, pp. 121-155.
Sukhatme, P. V., & Sukhatme, B. V. (1970). Sampling Theory of Surveys with Applications. Ames, IA: Iowa State.
Copyright (c) 2020 The Journal and the author
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.