IDENTIFIKASI TITIK HIGH LEVERAGE PADA MODEL REGRESI LOGISTIK DENGAN METODE ROBUST LOGISTIC DIAGNOSTIC
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2016-04-27
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Abstract
This article discusses the robust logistic diagnostic method for the identification of
high leverage points in logistic regression model which is a review of article from
Syaiba and Habshah [Journal of Applied Sciences, 10 (2010), 3042-3050]. On first
stage, robust estimator used to identify suspect high leverage points by computing
the robust Mahalanobis distance based on minimum covariance determinant and
minimum volume ellipsoid. On the second stage, the group deleted based on the
distance from the mean for logistic regression model is computed. Then the
effectiveness of this method is investigated through the simulation of data using
software R version 3.1.2.
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Keywords
Logistic regression model, outlier, high leverage, robust Mahalanobis distance, minimum covariance determinants, minimum volume ellipsoid