Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator

Stability selection (multisplit) approach is a variable selection procedure which relies on multisplit data to overcome the shortcomings that may occur to single-split data. Unfortunately, this procedure yields very poor results in the presence of outliers and other contamination in the original dat...

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Main Authors: Uraibi, Hassan S., Midi, Habshah, Rana, Sohel
Format: Article
Language:English
Published: Hindawi 2015
Online Access:http://psasir.upm.edu.my/id/eprint/46202/
http://psasir.upm.edu.my/id/eprint/46202/1/Robust%20stability%20best%20subset%20selection%20for%20autocorrelated%20data%20based%20on%20robust%20location%20and%20dispersion%20estimator.pdf
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author Uraibi, Hassan S.
Midi, Habshah
Rana, Sohel
author_facet Uraibi, Hassan S.
Midi, Habshah
Rana, Sohel
author_sort Uraibi, Hassan S.
building UPM Institutional Repository
collection Online Access
description Stability selection (multisplit) approach is a variable selection procedure which relies on multisplit data to overcome the shortcomings that may occur to single-split data. Unfortunately, this procedure yields very poor results in the presence of outliers and other contamination in the original data. The problem becomes more complicated when the regression residuals are serially correlated. This paper presents a new robust stability selection procedure to remedy the combined problem of autocorrelation and outliers. We demonstrate the good performance of our proposed robust selection method using real air quality data and simulation study.
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spelling upm-462022022-05-31T20:44:00Z http://psasir.upm.edu.my/id/eprint/46202/ Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator Uraibi, Hassan S. Midi, Habshah Rana, Sohel Stability selection (multisplit) approach is a variable selection procedure which relies on multisplit data to overcome the shortcomings that may occur to single-split data. Unfortunately, this procedure yields very poor results in the presence of outliers and other contamination in the original data. The problem becomes more complicated when the regression residuals are serially correlated. This paper presents a new robust stability selection procedure to remedy the combined problem of autocorrelation and outliers. We demonstrate the good performance of our proposed robust selection method using real air quality data and simulation study. Hindawi 2015 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/46202/1/Robust%20stability%20best%20subset%20selection%20for%20autocorrelated%20data%20based%20on%20robust%20location%20and%20dispersion%20estimator.pdf Uraibi, Hassan S. and Midi, Habshah and Rana, Sohel (2015) Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator. Journal of probability and Statistics, 2015. art. no. 432986. pp. 1-8. ISSN 1687-952X; ESSN: 1687-9538 https://www.hindawi.com/journals/jps/2015/432986/ 10.1155/2015/432986
spellingShingle Uraibi, Hassan S.
Midi, Habshah
Rana, Sohel
Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator
title Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator
title_full Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator
title_fullStr Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator
title_full_unstemmed Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator
title_short Robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator
title_sort robust stability best subset selection for autocorrelated data based on robust location and dispersion estimator
url http://psasir.upm.edu.my/id/eprint/46202/
http://psasir.upm.edu.my/id/eprint/46202/
http://psasir.upm.edu.my/id/eprint/46202/
http://psasir.upm.edu.my/id/eprint/46202/1/Robust%20stability%20best%20subset%20selection%20for%20autocorrelated%20data%20based%20on%20robust%20location%20and%20dispersion%20estimator.pdf