Variable selection via SCAD-penalized quantile regression for high-dimensional count data

• Main Authors: Muhammad Khan, Dost, Yaqoob, Anum, Iqbal, Nadeem, Abdul Wahid, Khalil, Umair, Khan, Mukhtaj, Abd Rahman, Mohd Amiruddin, Mustafa, Mohd Shafie, Khan, Zardad
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers 2019
• Online Access: http://psasir.upm.edu.my/id/eprint/82711/1/Variable%20selection%20.pdf; http://psasir.upm.edu.my/id/eprint/82711/; https://ieeexplore.ieee.org/document/8876588/authors#authors
• Institution: Universiti Putra Malaysia

This article introduces a quantile penalized regression technique for variable selection and estimation of conditional quantiles of counts in sparse high-dimensional models. The direct estimation and variable selection of the quantile regression is not feasible due to the discreteness of the count d...