Adaptive lasso for linear regression models with ARMA-GARCH errors

DOI10.1080/03610918.2015.1096372zbMath1368.62199OpenAlexW2176979681MaRDI QIDQ4976540

Sooyong Lee, Taewook Lee, Young Joo Yoon

Publication date: 31 July 2017

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2015.1096372

zbMATH Keywords

variable selectionpenalized regressionadaptive LassoARMA error modelsARMA-GARCH error models

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Point estimation (62F10)

Related Items (5)

Likelihood-based quantile autoregressive distributed lag models and its applications ⋮ Penalised inference for lagged dependent regression in the presence of autocorrelated residuals ⋮ Bayesian LASSO-Regularized quantile regression for linear regression models with autoregressive errors ⋮ Efficient estimation method for generalized ARFIMA models ⋮ Bayesian bridge-randomized penalized quantile regression estimation for linear regression model with AP(q) perturbation

Cites Work

• The Adaptive Lasso and Its Oracle Properties
• Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
• Sparsity considerations for dependent variables
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Sparsity and Smoothness Via the Fused Lasso
• A Joint Regression Variable and Autoregressive Order Selection Criterion
• Adaptive Lasso for Cox's proportional hazards model

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