scholarly journals Regression-in-Ratio Estimators for Population Mean by Using Robust Regression in Two Phase Sampling

Author(s):  
Aamir Raza ◽  
Muhammad Noor-ul-Amin

The estimation of population mean is not meaningful using ordinary least square method when data contains some outliers. In the current study, we proposed efficient estimators of population mean using robust regression in two phase sampling. An extensive simulation study is conduct to examine the efficiency of proposed estimators in terms of mean square error (MSE). Real life example and extensive simulation study are cited to demonstrate the performance of the proposed estimators. Theoretical example and simulation studies showed that the suggested estimators are more efficient than the considered estimators in the presence of outliers.

2020 ◽  
Vol 2 (1) ◽  
pp. 51-57
Author(s):  
Asifa Kamal ◽  
Nimra Amir ◽  
Huma Dastagir

This study is designed for predictive estimation of finite population mean in two phase sampling using two auxiliary variables. Two phase exponential ratio type estimator and exponential chain ratio type estimator are proposed under predictive approach suggested by Bahl & Tuteja (1991). The expressions of bias and mean square error of both suggested estimators have been carried out for theoretical comparison. The numerical study on real life data sets as well as simulation study has been conducted to examine the performance of suggested estimators. Finally, it is demonstrated that the suggested exponential ratio estimators are more efficient than competitive estimators in support of numerical and simulation study as well.


1995 ◽  
Vol 45 (3-4) ◽  
pp. 203-218 ◽  
Author(s):  
T. P. Tripathi ◽  
M. S. Ahmed

A class of estimators for a finite population mean is presented for the situations where population means of some auxiliary variables are known while those of others are unknown. The results for general two phase sampling are indicated while the detailed discussion is made for the case when SRSWOR is used at both the phases. While several known estimators belong to the proposed clas~ some new estimators are identified as well. The optimum estimator in the proposed class is found to be better than the so-called chain ratio and regression estimators discu ssed by Chand (1975). Kiregyera (1984) and Mukerjee et al. (1987). The relative gains in efficiency of tho proposed optimum estimator over the others are obtained for a natural population data and found to be quite appreciable.


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