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

  • Aamir Raza Department of Statistics, Graduate College, Mandi Bahauddin, Pakistan
  • Muhammad Noor-ul-Amin COMSATS University Islamabad-Lahore Campus, Pakistan
Keywords: Auxiliary Information, M-Estimator, Outliers, Robust Regression, Two Phase Sampling

Abstract

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.

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Author Biographies

Aamir Raza, Department of Statistics, Graduate College, Mandi Bahauddin, Pakistan

Aamir Raza received his Ph.D. degree from National College of Business Administration & Economics (NCBA&E), Lahore, Pakistan. He did his M. Phil & M.Sc. Statistics from University of the Punjab, Lahore. He is currently working as Lecturer in Statistics at Govt. Graduate College, Mandi Bahauddin. His research interests include sampling techniques and Robust Regression.

Muhammad Noor-ul-Amin, COMSATS University Islamabad-Lahore Campus, Pakistan

Muhammad Noor-ul-Amin received his Ph.D. degree from NCBA&E, Lahore, Pakistan. He has working experience in various universities for teaching and research that includes the Virtual University of Pakistan, University of Sargodha, Pakistan, and the University of Burgundy, France. He is currently working as an Assistant Professor at COMSATS University Islamabad-Lahore Campus. His research interests include sampling techniques and control charting techniques. He is an HEC approved supervisor.

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Published
2021-10-14
Section
Articles