Square-Root LASSO for High-Dimensional Sparse Linear Systems with Weakly Dependent Errors-Reference-Cited by-同舟云学术

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Square-Root LASSO for High-Dimensional Sparse Linear Systems with Weakly Dependent Errors

Published:2017-12-11 Issue:2 Volume:39 Page:212-238
ISSN:0143-9782
Container-title:Journal of Time Series Analysis
language:en
Short-container-title:J. Time Ser. Anal.

Author:

Xie Fang¹²,Xiao Zhijie³⁴

Affiliation:

1. Department of Mathematics, Faculty of Science and Technology; University of Macau; Taipa China

2. UM Zhuhai Research Institute; Zhuhai China

3. Department of Economics; Boston College; Chestnut Hill MA USA

4. Center for Economic Research; Shandong University; Jinan China

Funder

NNSFC

Macao S.A.R.

Universidade de Macau

Boston College

National Natural Science Foundation of China

Publisher

Wiley

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/jtsa.12278/fullpdf

Reference26 articles.

1. Central limit theorems for empirical and U-processes of stationary mixing sequences;Arcones;Journal of Theoretical Probability,1994

2. Square-root Lasso: pivotal recovery of sparse signals via conic programming;Belloni;Biometrika,2011

3. Regularized estimation in sparse high-dimensional time series models;Basu;Annals of Statistics,2015

4. Forecasting economic time series using targeted predictors;Bai;Journal of Econometrics,2008

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