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A new robust diagnostic plot for classifying good and bad high leverage points in a multiple linear regression model

Alguraibawi, Mohammed and Midi, Habshah and Rahmatullah Imon, A. H. M. (2015) A new robust diagnostic plot for classifying good and bad high leverage points in a multiple linear regression model. Mathematical Problems in Engineering, 2015 . pp. 1-12. ISSN 1024-123X

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Abstract

Identification of high leverage point is crucial because it is responsible for inaccurate prediction and invalid inferential statement as it has a larger impact on the computed values of various estimates. It is essential to classify the high leverage points into good and bad leverage points because only the bad leverage points have an undue effect on the parameter estimates. It is now evident that when a group of high leverage points is present in a data set, the existing robust diagnostic plot fails to classify them correctly. This problem is due to the masking and swamping effects. In this paper, we propose a new robust diagnostic plot to correctly classify the good and bad leverage points by reducing both masking and swamping effects. The formulation of the proposed plot is based on the Modified Generalized Studentized Residuals. We investigate the performance of our proposed method by employing a Monte Carlo simulation study and some well-known data sets. The results indicate that the proposed method is able to improve the rate of detection of bad leverage points and also to reduce swamping and masking effects.

Item Type:Article
Keyword:Robust diagnostic; Multiple linear
Faculty or Institute:Institute for Mathematical Research
Publisher:Hindawi Publishing Corporation
DOI Number:10.1155/2015/279472
Altmetrics:httphttp://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1155/2015/279472
ID Code:43528
Deposited By: Mohd Hafiz Che Mahasan
Deposited On:29 Jun 2016 09:10
Last Modified:29 Jun 2016 09:10

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