Regularized Estimation in High-Dimensional Vector Auto-Regressive Models Using Spatio-Temporal Information
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Publication:6069868
DOI10.5705/ss.202020.0056arXiv2012.10030WikidataQ114013841 ScholiaQ114013841MaRDI QIDQ6069868
Zhengyuan Zhu, Abolfazl Safikhani, Unnamed Author, David S. Matteson
Publication date: 17 November 2023
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2012.10030
Cites Work
- Unnamed Item
- Regularized estimation in sparse high-dimensional time series models
- Factor modeling for high-dimensional time series: inference for the number of factors
- Selection of spatial-temporal lattice models: assessing the impact of climate conditions on a mountain pine beetle outbreak
- Sparse seasonal and periodic vector autoregressive modeling
- Nonconcave penalized estimation in sparse vector autoregression model
- Autoregressive models for gene regulatory network inference: sparsity, stability and causality issues
- Dynamic Orthogonal Components for Multivariate Time Series
- Low Rank and Structured Modeling of High-Dimensional Vector Autoregressions
- Stability Selection
- Local Polynomial Kernel Regression for Generalized Linear Models and Quasi-Likelihood Functions
- Regression coefficient and autoregressive order shrinkage and selection via the lasso
- Error-Correction Factor Models for High-dimensional Cointegrated Time Series
- Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$-Balls
- Tuning parameter selectors for the smoothly clipped absolute deviation method
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