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A New Regression Type Estimator with Two Auxiliary Variables for Single-Phase Sampling
Department of Statistics and Actuarial Science, Kenyatta University, Nairobi, Kenya
Department of Statistics and Actuarial Science, Kenyatta University, Nairobi, Kenya
Department of Statistics and Actuarial Science, Kenyatta University, Nairobi, Kenya
- 1 Department of Statistics and Actuarial Science, Kenyatta University, Nairobi, Kenya
- 2 Department of Statistics and Actuarial Science, Kenyatta University, Nairobi, Kenya
- 3 Department of Statistics and Actuarial Science, Kenyatta University, Nairobi, Kenya
Open Journal of Statistics·Volume 04 (2014)·Pages 789–796·Published 13 October 2014·DOI10.4236/ojs.2014.49074
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Abstract
In this paper, we have proposed an estimator of finite population mean using a new regression type estimator with two auxiliary variables for single-phase sampling and investigated its finite sample properties. An empirical study has been carried out to compare the performance of the proposed estimator with the existing estimators that utilize auxiliary variables for finite population mean. It has been found that the new regression type estimator with two auxiliary variables for to be more efficient than mean per unit, ratio and product estimator and exponential ratio and exponential product estimators and exponential ratio-product estimator.
KeywordsRegression EstimatorExponential Ratio-Product EstimatorAuxiliary VariablesMean Squared Error
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