Subset selection for vector autoregressive processes using Lasso

DOI10.1016/j.csda.2007.12.004zbMath1359.62296OpenAlexW1996703612MaRDI QIDQ1023702

Nan-Jung Hsu, Hung-Lin Hung, Ya-Mei Chang

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.12.004

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

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Uses Software

• PcGets
• FinTS

Cites Work

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• The Adaptive Lasso and Its Oracle Properties
• Multivariate subset autoregressive modelling with zero constraints for detecting 'overall causality'
• Estimating the dimension of a model
• Model reduction methods for vector autoregressive processes.
• Asymptotics for Lasso-type estimators.
• Least angle regression. (With discussion)
• Order determination for multivariate autoregressive processes using resampling methods
• ON THE RECURSIVE FITTING OF SUBSET AUTOREGRESSIONS
• The Multivariate Portmanteau Statistic
• Modeling Multiple Times Series with Applications
• A Unified Approach to Identifying Multivariate Time Series Models
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Modeling Satellite Ozone Data
• Regression coefficient and autoregressive order shrinkage and selection via the lasso
• Computer automation of general-to-specific model selection procedures
• A new look at the statistical model identification

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