Mir Subzar , S. Maqbool , T. A. Raja , Prayas Sharma
ARTICLE

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ABSTRACT

The most dominant problem in the survey sampling is to obtain the better ratio estimators for the estimation of population mean or population variance. Estimation theory is enhanced by using the auxiliary information in order to improve on designs, precision and efficiency of estimators. A modified class of ratio estimator is suggested in this paper to estimate the population mean. Expressions for the bias and the mean square error of the proposed estimators are obtained. Both analytical and numerical comparison has shown the suggested estimator to be more efficient than some existing ones. The bias of the suggested estimator is also found to be negligible for the population under consideration, indicating that the estimator is as good the regression estimator and better than the other estimators under consideration.

KEYWORDS

ratio type estimators, auxiliary information, bias, mean square error, simple random sampling, efficiency

REFERENCES

COCHRAN, W. G., (1940). The estimation of the yields of the cereal experiments by sampling for the ratio of grain to total produce. Journal of Agricultural Science, 30, pp. 262–275.

KADILAR, C., CINGI, H., (2004). Ratio estimators in simple random sampling. Applied Mathematics and Computation, 151, pp. 893–902.

MURTHY, M. N., (1967). Sampling theory and methods, Statistical Publishing Society, Calcutta, India.

SINGH, D., CHAUDHARY, F. S., (1986). Theory and Analysis of Sample Survey Designs, New Age International Publisher.

SUBRAMANI, J., KUMARAPANDIYAN, G., (2012). Estimation of population mean using known median and co-efficient of skewness. American Journal of Mathematics and Statistics, 2(5), pp. 101–107.

ROBSON, D. S., (1957). Application of multivariate Polykays to the theory of unbiased ratio type estimation. Journal of American Statistical Association, 52, pp. 411–422.

OKAFOR, F. C., (2002). Sample Survey Theory with Applications (1st ed.), N sukka, Nigeria, Afro-Orbis.

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, pp. 193–196.

RAJESH, T., RAJESH, P., JONG-MIND, K., (2011). Ratio-cum-product Estimators of Population mean using known Parameters of Auxiliary Variables. Communications of the Korean Statistical Society, 18(2), pp. 155–164.

SHARMA, P., SINGH, R., (2014). Improved Ratio Type Estimators Using Two Auxiliary Variables under Second Order Approximation, Mathematical Journal of Interdisciplinary Sciences, Vol. 2, No. 2, pp. 193–204.

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