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The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression

Leverage values are being used in regression diagnostics as measures of influential observations in the $X$-space. Detection of high leverage values is crucial because of their responsibility for misleading conclusion about the fitting of a regression model, causing multicollinearity problems, maski...

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Main Authors: Midi, Habshah, Mohamed Ramli, Norazan, Imon, A. H. M. Rahmatullah
Format: Article
Language:English
Published: Taylor & Francis 2009
Online Access:http://psasir.upm.edu.my/id/eprint/17260/1/The%20performance%20of%20diagnostic.pdf
http://psasir.upm.edu.my/id/eprint/17260/
http://www.tandfonline.com/doi/abs/10.1080/02664760802553463#.VeT8bZdrsZM
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spelling my.upm.eprints.172602015-10-23T02:49:29Z http://psasir.upm.edu.my/id/eprint/17260/ The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression Midi, Habshah Mohamed Ramli, Norazan Imon, A. H. M. Rahmatullah Leverage values are being used in regression diagnostics as measures of influential observations in the $X$-space. Detection of high leverage values is crucial because of their responsibility for misleading conclusion about the fitting of a regression model, causing multicollinearity problems, masking and/or swamping of outliers, etc. Much work has been done on the identification of single high leverage points and it is generally believed that the problem of detection of a single high leverage point has been largely resolved. But there is no general agreement among the statisticians about the detection of multiple high leverage points. When a group of high leverage points is present in a data set, mainly because of the masking and/or swamping effects the commonly used diagnostic methods fail to identify them correctly. On the other hand, the robust alternative methods can identify the high leverage points correctly but they have a tendency to identify too many low leverage points to be points of high leverages which is not also desired. An attempt has been made to make a compromise between these two approaches. We propose an adaptive method where the suspected high leverage points are identified by robust methods and then the low leverage points (if any) are put back into the estimation data set after diagnostic checking. The usefulness of our newly proposed method for the detection of multiple high leverage points is studied by some well-known data sets and Monte Carlo simulations. Taylor & Francis 2009 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/17260/1/The%20performance%20of%20diagnostic.pdf Midi, Habshah and Mohamed Ramli, Norazan and Imon, A. H. M. Rahmatullah (2009) The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression. Journal of Applied Statistics, 36 (5). pp. 507-520. ISSN 0266-4763; ESSN: 1360-0532 http://www.tandfonline.com/doi/abs/10.1080/02664760802553463#.VeT8bZdrsZM 10.1080/02664760802553463
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Leverage values are being used in regression diagnostics as measures of influential observations in the $X$-space. Detection of high leverage values is crucial because of their responsibility for misleading conclusion about the fitting of a regression model, causing multicollinearity problems, masking and/or swamping of outliers, etc. Much work has been done on the identification of single high leverage points and it is generally believed that the problem of detection of a single high leverage point has been largely resolved. But there is no general agreement among the statisticians about the detection of multiple high leverage points. When a group of high leverage points is present in a data set, mainly because of the masking and/or swamping effects the commonly used diagnostic methods fail to identify them correctly. On the other hand, the robust alternative methods can identify the high leverage points correctly but they have a tendency to identify too many low leverage points to be points of high leverages which is not also desired. An attempt has been made to make a compromise between these two approaches. We propose an adaptive method where the suspected high leverage points are identified by robust methods and then the low leverage points (if any) are put back into the estimation data set after diagnostic checking. The usefulness of our newly proposed method for the detection of multiple high leverage points is studied by some well-known data sets and Monte Carlo simulations.
format Article
author Midi, Habshah
Mohamed Ramli, Norazan
Imon, A. H. M. Rahmatullah
spellingShingle Midi, Habshah
Mohamed Ramli, Norazan
Imon, A. H. M. Rahmatullah
The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression
author_facet Midi, Habshah
Mohamed Ramli, Norazan
Imon, A. H. M. Rahmatullah
author_sort Midi, Habshah
title The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression
title_short The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression
title_full The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression
title_fullStr The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression
title_full_unstemmed The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression
title_sort performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression
publisher Taylor & Francis
publishDate 2009
url http://psasir.upm.edu.my/id/eprint/17260/1/The%20performance%20of%20diagnostic.pdf
http://psasir.upm.edu.my/id/eprint/17260/
http://www.tandfonline.com/doi/abs/10.1080/02664760802553463#.VeT8bZdrsZM
_version_ 1643826462858412032
score 13.211869

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