Group Identification and Variable Selection in Quantile Regression
Joint Authors
Alkenani, Ali
Msallam, Basim Shlaibah
Source
Journal of Probability and Statistics
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-10
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Using the Pairwise Absolute Clustering and Sparsity (PACS) penalty, we proposed the regularized quantile regression QR method (QR-PACS).
The PACS penalty achieves the elimination of insignificant predictors and the combination of predictors with indistinguishable coefficients (IC), which are the two issues raised in the searching for the true model.
QR-PACS extends PACS from mean regression settings to QR settings.
The paper shows that QR-PACS can yield promising predictive precision as well as identifying related groups in both simulation and real data.
American Psychological Association (APA)
Alkenani, Ali& Msallam, Basim Shlaibah. 2019. Group Identification and Variable Selection in Quantile Regression. Journal of Probability and Statistics،Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1186874
Modern Language Association (MLA)
Alkenani, Ali& Msallam, Basim Shlaibah. Group Identification and Variable Selection in Quantile Regression. Journal of Probability and Statistics No. 2019 (2019), pp.1-7.
https://search.emarefa.net/detail/BIM-1186874
American Medical Association (AMA)
Alkenani, Ali& Msallam, Basim Shlaibah. Group Identification and Variable Selection in Quantile Regression. Journal of Probability and Statistics. 2019. Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1186874
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186874