Automated Estimation of Heavy-Tailed Vector Error Correction Models

DOI10.5705/ss.202020.0177OpenAlexW4200320761WikidataQ114013838 ScholiaQ114013838MaRDI QIDQ5041351

Shiqing Ling, Zichuan Mi, Feifei Guo

Publication date: 13 October 2022

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.202020.0177

zbMATH Keywords

cointegrationLassoheavy-tailedreduced rank LSE

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Inference for the VEC(1) model with a heavy-tailed linear process errors* ⋮ Inference in heavy-tailed vector error correction models

Cites Work

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• Regularized estimation in sparse high-dimensional time series models
• The Adaptive Lasso and Its Oracle Properties
• A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems
• A specification test for nonlinear nonstationary models
• Oracle inequalities for high dimensional vector autoregressions
• Subset ARMA selection via the adaptive Lasso
• Limit theory for moving averages of random variables with regularly varying tail probabilities
• Limit theory for the sample covariance and correlation functions of moving averages
• Statistical analysis of cointegration vectors
• Weak limit theorems for stochastic integrals and stochastic differential equations
• Asymptotics for linear processes
• Tests for cointegration with infinite variance errors
• Heavy tail modeling and teletraffic data. (With discussions and rejoinder)
• Determination of vector error correction models in high dimensions
• Asymptotics for Lasso-type estimators.
• Variable selection for Cox's proportional hazards model and frailty model
• Parameter estimation for ARMA models with infinite variance innovations
• Inference in heavy-tailed vector error correction models
• CONSISTENT AND CONSERVATIVE MODEL SELECTION WITH THE ADAPTIVE LASSO IN STATIONARY AND NONSTATIONARY AUTOREGRESSIONS
• ASYMPTOTIC INFERENCE FOR AR MODELS WITH HEAVY-TAILED G-GARCH NOISES
• Estimation for Partially Nonstationary Multivariate Autoregressive Models
• Point processes, regular variation and weak convergence
• Multiple Time Series Regression with Integrated Processes
• Nested Reduced-Rank Autogressive Models for Multiple Time Series
• Likelihood-Based Inference in Cointegrated Vector Autoregressive Models
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Probability
• Bootstrap Testing of Hypotheses on Co-Integration Relations in Vector Autoregressive Models
• VECTOR AUTOREGRESSIVE MODELS WITH UNIT ROOTS AND REDUCED RANK STRUCTURE:ESTIMATION. LIKELIHOOD RATIO TEST, AND FORECASTING
• Co-Integration and Error Correction: Representation, Estimation, and Testing
• TESTING AND INFERENCE IN NONLINEAR COINTEGRATING VECTOR ERROR CORRECTION MODELS
• Lasso-based Variable Selection of ARMA Models
• Regression coefficient and autoregressive order shrinkage and selection via the lasso
• AUTOMATED ESTIMATION OF VECTOR ERROR CORRECTION MODELS
• Model Selection and Estimation in Regression with Grouped Variables