TINGKAT EFISIENSI PENAKSIR M TERHADAP PENAKSIR LMS DALAM MENAKSIR KOEFISIEN GARIS REGRESI
Keywords: efficiency, LMS estimator, M estimator, outlier, robust regression
Abstract
The using of OLS method to estimate the regression coefficients in multiple linear regression model presupposed assumption that there is no outlier in the data. Alternatively, robust regression methods can be used. This paper aims to investigate the efficiency of M method and LMS method to estimate the regression coefficients. Besides application data, simulation data generated by MINITAB and SYSTAT package program were used. The investigation shows the LMS method is more efficient than the M method when there is outlier in the data. Otherwise, the M method is more efficient than the LMS method.
Downloads
References
Myers, R.H. (1990). Classical and modern regression with applications (2nd ed). Boston: PWS- Kent.
Rousseeuw, P.J. & Leroy,A.M. (2003). Robust regression and outlier detection. New York: Wiley.
Staudte, R.G. & Sheather, S.J. (1990). Robust estimation and testing. New York: Wiley.
Sugiarti, H. (2008). Resistensi dan efisiensi fungsi pembobot Huber pada metode regresi robust. Makalah pada Konferensi Nasional Matematika XIV tanggal 24-27 Juli 2008 di Universitas Sriwijaya, Palembang.
Wackerly,D.D., Mendenhall,W. & Scheaffer,R.L. (2008). Mathematical statistics with applications (7th ed). Duxbury: Thomson.
Copyright (c) 2010 Jurnal Matematika Sains dan Teknologi

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.