Class of Difference Cum Ratio–Type Estimator in Double Sampling Using Two Auxiliary Variables with Some Known Population Parameters
American Journal of Theoretical and Applied Statistics
Volume 8, Issue 1, January 2019, Pages: 31-38
Received: Feb. 2, 2019;
Accepted: Mar. 12, 2019;
Published: Apr. 1, 2019
Views 612 Downloads 133
Akingbade Toluwalase Janet, Department of Statistics, Faculty of Physical Sciences, University of Nigeria, Nsukka, Nigeria
Okafor Fabian Chinemelu, Department of Statistics, Faculty of Physical Sciences, University of Nigeria, Nsukka, Nigeria
In this paper, a class of double sampling difference cum ratio - type estimator using two auxiliary variables was proposed for estimating the finite population mean of the variable of interest. The expression for the bias and the mean square error of the proposed estimators are derived; in addition, some members of the class of the estimator are identified. The conditions under which the proposed estimators perform better than the sample mean and the existing double sampling ratio type estimators are derived. The empirical analysis showed that the proposed class of estimator performs better than the existing estimators considered in this study.
Akingbade Toluwalase Janet,
Okafor Fabian Chinemelu,
Class of Difference Cum Ratio–Type Estimator in Double Sampling Using Two Auxiliary Variables with Some Known Population Parameters, American Journal of Theoretical and Applied Statistics.
Vol. 8, No. 1,
2019, pp. 31-38.
Kadilar, C. & Cingi, H. (2004), Ratio estimators in simple random sampling’, Applied Mathematics and Computation 151(3), 893–902.
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), 103–109.
Raja, T. A., Subair, M., Maqbool, S. &Hakak, A.(2017) Enhancing the Mean Ratio Estimator for Estimating Population Mean Using Conventional Parameters; International Journal of Mathematics and Statistics Invention (IJSM)5(1),58-61.
Sisodia, B. V. S. &Dwivedi, V. K.(1981) ‘A modified ratio estimator using coefficient of variation of auxiliary variable Journal of the Indian Society of Agricultural Statistics 33(1),13–18.
Singh, H. P. & Kakran, M. S. (1993).: A modified ratio estimator using known coefficient of kurtosis of an auxiliary character. Revised version submitted to Journal of Indian Society of Agricultural Statistics, New Delhi, India.
Singh, H. P. & Tailor, R. (2003), Use of known correlation coefficient in estimating the finite population means Statistics in Transition 6(4), 555–560.
Subramani, J. &Kumarapandiyan, G.(2013)Estimation Of Finite Population Mean Using Decilesof an Auxiliary VariableStatistics in Transition-new series, Spring 2013 Vol. 14, No. 1, pp. 75–88.
Upadhyaya, L. N. & Singh, H.(1999) Use of transformed auxiliary variable in estimating the finite population mean Biometrical Journal 41(5), 627–636.
Yan, Z. &Tian, B., (2010). Ratio Method to the Mean Estimation Using Coefficient of Skewness of Auxiliary Variable, ICICA 2010, Part II, CCIS 106, pp. 103-110.
Cochran W. G. (1977), Sampling Techniques, 3rd edition, Wiley Eastern Limited, New York.
Kadilar, C., &Cingi, H. (2005). A new estimator using two auxiliary variables. Applied Mathematics and Computation, 162, 901-908.
Mohanty, S.,(1967) Combination of regression and ratio estimate. J. Ind. Statist., 5:16-19.
Olkin, I. (1958). Multivariate ratio estimation for finite populations. Biometrika, 45: 154-165.
Singh, M. P. (1965). On the estimation of ratio and product of population parameters, Sankhya, Series C, 27, 321-328.
Swain A. K. P. C. (2012), On Classes Of Modified Ratio Type and Regression-Cum-RatioTypeEstimators In Sample Surveys Using Two Auxiliary Variables Statistics In Transition-New series, Vol. 13, No. 3, pp. 473—494.
Mukerjee, R., Rao T. J., &Vijayan, K., (1987), Regression type estimators using multiple auxiliary information. Austral. J. Statist., 29(3):244-254.
Muhammad, H., Naqvi, H. & Muhammad Q. S., (2010)Some new regression type estimators in two phase sampling, World Applied Science Journal., 8(7):799-803.
Tripathi, T. P., Das, A. K. & Khare, B. B., (1994). ‘Use of Auxiliary Information in Sample Surveys-A Review’ Aligarh Journal of Statistics, 14, 79-134.
Chattefuee&Hadi (2006), Regression Analysis by Example, 4th edition, New York, John Wiley &Sons.