Sparse quantile regression via ℓ０-penalty

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Note (General)：: Honda’s research is supported by JSPS KAKENHI Grant Number JP20K11705.

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Material Type: 文書・図像類
Title: Sparse quantile regression via ℓ０-penalty
Author/Editor: 本田, 敏雄
Author Heading: 本田, 敏雄
https://nrid.nii.ac.jp/nrid/1000030261754/
Publication, Distribution, etc.: Graduate School of Economics, Hitotsubashi University
Publication Date: 2023-11-01
Publication Date (W3CDTF): 2023-11-01
Text Language Code: eng
Subject Heading: selection consistency
high-dimensional information criteria
B-spline basis
additive models
varying coefficient models
Target Audience: 一般
Note (General): Honda’s research is supported by JSPS KAKENHI Grant Number JP20K11705.
Periodical Title: Discussion papers ; No. 2023-03
Continues: HDL : This version has been revised. The new version is available at https://hdl.handle.net/10086/81451.
https://hdl.handle.net/10086/81451
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 一橋大学 : HERMES-IR(一橋大学機関リポジトリ) : Research & Education Resources