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Mixture Regression-Cum-Ratio Estimator Using Multi-Auxiliary Variables and Attributes in Single-Phase Sampling

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DOI: 10.4236/ojs.2014.45036    3,049 Downloads   3,557 Views   Citations

ABSTRACT

In this paper, we have proposed a class of mixture regression-cum-ratio estimator for estimating population mean by using information on multiple auxiliary variables and attributes simultaneously in single-phase sampling and analyzed the properties of the estimator. An empirical was carried out to compare the performance of the proposed estimator with the existing estimators of finite population mean using simulated population. It was found that the mixture regression-cum-ratio estimator was more efficient than ratio and regression estimators using one auxiliary variable and attribute, ratio and regression estimators using multiple auxiliary variables and attributes and regression-cum-ratio estimators using multiple auxiliary variables and attributes in single-phase sampling for finite population.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Mutembei, T. , Kung’u, J. and Ouma, C. (2014) Mixture Regression-Cum-Ratio Estimator Using Multi-Auxiliary Variables and Attributes in Single-Phase Sampling. Open Journal of Statistics, 4, 367-376. doi: 10.4236/ojs.2014.45036.

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