Forward variable selection for ultra-high dimensional quantile regression models

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Note (General)：: First version : August 2021, Second version：January 2022, This version：May 2022Honda’s research was supported in part by JSPS KAKENHI Grant Number JP ...

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Material Type: 文書・図像類
Title: Forward variable selection for ultra-high dimensional quantile regression models
Author/Editor: 本田, 敏雄
Lin, Chien-Tong
Author Heading: 本田, 敏雄
https://nrid.nii.ac.jp/nrid/1000030261754/
Lin, Chien-Tong
Publication, Distribution, etc.: Graduate School of Economics, Hitotsubashi University
Publication Date: 2022-05
Publication Date (W3CDTF): 2022-05
Text Language Code: eng
Subject Heading: forward procedure
check function
sparsity
screening consistency
stopping rule
Target Audience: 一般
Note (General): First version : August 2021, Second version：January 2022, This version：May 2022
Honda’s research was supported in part by JSPS KAKENHI Grant Number JP 20K11705, Japan.
Lin’s research was supported by Science Vanguard Research Program of the Ministry of Science and Technology, Taiwan.
Format (IMT): application/pdf
Source: fulltext
https://hermes-ir.lib.hit-u.ac.jp/hermes/ir/re/74078/070econDP21-02.pdf
Access Restrictions: インターネット公開
Periodical Title: Discussion papers ; No. 2021-02
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