Exponential Ratio Type Estimators In Stratified Random Sampling

Source: arXiv

ABSTRACT Kadilar and Cingi (2003) have introduced a family of estimators using
auxiliary information in stratified random sampling. In this paper, we propose
the ratio estimator for the estimation of population mean in the stratified
random sampling by using the estimators in Bahl and Tuteja (1991) and Kadilar
and Cingi (2003). Obtaining the mean square error (MSE) equations of the
proposed estimators, we find theoretical conditions that the proposed
estimators are more efficient than the other estimators. These theoretical
findings are supported by a numerical example.

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    ABSTRACT: This is an eclectic tome of 100 papers in various fields of sciences, alphabetically listed, such as: astronomy, biology, calculus, chemistry, computer programming codification, economics and business and politics, education and administration, game theory, geometry, graph theory, information fusion, neutrosophic logic and set, non-Euclidean geometry, number theory, paradoxes, philosophy of science, psychology, quantum physics, scientific research methods, and statistics – containing 800 pages. It was my preoccupation and collaboration as author, co-author, translator, or co-translator, and editor with many scientists from around the world for long time. Many ideas from this book are to be developed and expanded in future explorations.
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    ABSTRACT: The objective of the present paper is to propose a family of separate-type estimators of population mean in stratified random sampling in presence of non-response based on the family of estimators proposed by Khoshnevisan et al. (2007). Under simple random sampling without replacement (SRSWOR) the expressions of bias and mean square error (MSE) up to the first order of approximation are derived. The comparative study of the family with respect to usual estimator has been discussed. The expressions for optimum sample sizes of the strata in respect to cost of the survey have also been derived. An empirical study is carried out to shoe the properties of the estimators.
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    ABSTRACT: In this article we have considered the problem of estimating the population mean in the stratified random sampling using the information of an auxiliary variable x which is correlated with y and suggested improved exponential ratio estimators in the stratified random sampling. The mean square error (MSE) equations for the proposed estimators have been derived and it is shown that the proposed estimators under optimum condition performs better than estimators suggested by Singh et al. (2008). Theoretical and empirical findings are encouraging and support the soundness of the proposed estimators for mean estimation.
    Pakistan Journal of Statistics and Operation Research. 01/2010;


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May 29, 2014