Notiragayu, notiragayu and Nisa, Khoirin (2008) ANALISIS REGRESI KOMPONEN UTAMA ROBUST UNTUK DATA MENGANDUNG PENCILAN. J. Sains MIPA, 14 (1). pp. 45-50. ISSN ISSN 1978-1873

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Principal Component Regression (PCR) is one of the widely used statistical techniques for regression analysis with colinearity, and a robust technique on PCR when data contains outlier is an important problem. In this paper we consider the problem of robust PCR based on Minimum Volume Ellipsoid (MVE) estimator and Least Trimmed Square (LTS) regression. We aimed to look at the behavior of the principal component regression coefficient resulted by MVE-LTS and compare them with classical estimator through the bias and the mean square error. The result shows that PCR using MVE-LTS is very robust.

Item Type: Article
Subjects: H Social Sciences > HA Statistics
Depositing User: DR. KHOIRIN NISA
Date Deposited: 27 Mar 2018 04:42
Last Modified: 27 Mar 2018 04:42

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