Variable selection for high-dimensional regression models with time series and heteroscedastic errors-Reference-Cited by-同舟云学术

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Variable selection for high-dimensional regression models with time series and heteroscedastic errors

Published:2020-05 Issue:1 Volume:216 Page:118-136
ISSN:0304-4076
Container-title:Journal of Econometrics
language:en
Short-container-title:Journal of Econometrics

Author:

Chiou Hai-Tang,Guo Meihui,Ing Ching-Kang

Funder

Ministry of Science and Technology (MOST) of Taiwan

MOST of Taiwan

Publisher

Elsevier BV

Subject

Applied Mathematics,Economics and Econometrics

Reference26 articles.

1. Regularized estimation in sparse high-dimensional time series models;Basu;Ann. Statist.,2015

2. Pivotal estimation via square-root Lasso in nonparametric regression;Belloni;Ann. Statist.,2014

3. Intervention analysis with applications to economic and environmental problems;Box;J. Amer. Statist. Assoc.,1975

4. Big data analytics for modeling WAT parameter variation induced by process tool in semiconductor manufacturing and empirical study;Chien,2016

5. High-dimensional heteroscedastic regression with an application to eQTL data analysis;Daye;Biometrics,2012

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Estimation and variable selection for high-dimensional spatial dynamic panel data models;Journal of Econometrics;2024-01

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