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Robust Stability Best Subset Selection for Autocorrelated Data Based on Robust Location and Dispersion Estimator
Joint Authors
Midi, Habshah
Rana, Sohel
Uraibi, Hassan S.
Source
Journal of Probability and Statistics
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-31
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Uraibi, Hassan S.& Midi, Habshah& Rana, Sohel. 2015. Robust Stability Best Subset Selection for Autocorrelated Data Based on Robust Location and Dispersion Estimator. Journal of Probability and Statistics،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1069995
Modern Language Association (MLA)
Uraibi, Hassan S.…[et al.]. Robust Stability Best Subset Selection for Autocorrelated Data Based on Robust Location and Dispersion Estimator. Journal of Probability and Statistics No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1069995
American Medical Association (AMA)
Uraibi, Hassan S.& Midi, Habshah& Rana, Sohel. Robust Stability Best Subset Selection for Autocorrelated Data Based on Robust Location and Dispersion Estimator. Journal of Probability and Statistics. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1069995
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1069995