IJPAM: Volume 91, No. 3 (2014)
IN ROBUST REGRESSION
Sri Sulistijowati H., Twenty Liana
Sebelas Maret University
Jl. Ir. Sutami 36A Surakarta, INDONESIA
Assessment Institute for Agricultural Technology of
Kalimantan Tengah, Jl. G. Obos Km. 5
Abstract. In regression analysis the use of least squares method would not be appropriate in solving problem containing outlier or extreme observations. So we need a parameter estimation method which is robust where the value of the estimation is not much affected by small changes in the data. In this paper we present M estimation, S estimation and MM estimation in robust regression to determine a regression model. M estimation is an extension of the maximum likelihood method and is a robust estimation, while S estimation and MM estimation are the development of M estimation method. The algorithm of these methods is presented and then we apply them on the maize production data.
Received: November 14, 2013
AMS Subject Classification: 62J05, 62G35
Key Words and Phrases: robust regression, M estimation, S estimation, MM estimation
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DOI: 10.12732/ijpam.v91i3.7 How to cite this paper?
Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395