scientific article; zbMATH DE number 7306867
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Publication:5148950
David S. Matteson, Ines Wilms, Jacob Bien, William B. Nicholson
Publication date: 5 February 2021
Full work available at URL: https://arxiv.org/abs/1412.5250
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Related Items (8)
Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions ⋮ Forecasting vector autoregressions with mixed roots in the vicinity of unity ⋮ The EAS approach for graphical selection consistency in vector autoregression models ⋮ Regularized Estimation in High-Dimensional Vector Auto-Regressive Models Using Spatio-Temporal Information ⋮ Collective Anomaly Detection in High-Dimensional Var Models ⋮ Hierarchical sparse modeling: a choice of two group Lasso formulations ⋮ Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages ⋮ Confidence intervals for parameters in high-dimensional sparse vector autoregression
Uses Software
Cites Work
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- Generation Of Time Series Models With Given Spectral Properties
- The Model Confidence Set
- Regularized estimation in sparse high-dimensional time series models
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- A lasso for hierarchical interactions
- Relaxed Lasso
- Subset selection for vector autoregressive processes using Lasso
- Hierarchical sparse modeling: a choice of two group Lasso formulations
- Bayesian compressed vector autoregressions
- Theoretical properties of the overlapping groups Lasso
- Selection in VAR-models using equal and unequal lag-length procedures
- Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors
- Large time-varying parameter VARs
- Fitting autoregressive models for prediction
- Dynamic Orthogonal Components for Multivariate Time Series
- Regression and time series model selection in small samples
- A canonical analysis of multiple time series
- Forecasting Using Principal Components From a Large Number of Predictors
- Low Rank and Structured Modeling of High-Dimensional Vector Autoregressions
- Group Regularized Estimation Under Structural Hierarchy
- Variable Selection Using Adaptive Nonlinear Interaction Structures in High Dimensions
- Learning Local Dependence In Ordered Data
- Model Selection and Estimation in Regression with Grouped Variables
- Estimation of parameters and eigenmodes of multivariate autoregressive models
- Lag length estimation in large dimensional systems
- Determining the Number of Factors in Approximate Factor Models
- The Generalized Dynamic Factor Model
- Structured sparsity through convex optimization
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