Regularized joint estimation of related vector autoregressive models
DOI10.1016/j.csda.2019.05.007OpenAlexW2944887819WikidataQ90444922 ScholiaQ90444922MaRDI QIDQ2002726
Publication date: 12 July 2019
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079674
group Lassoregularized estimationvector autoregressionstability selectionattention deficit hyperactivity disorderresting-state fMRI
Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Ridge regression; shrinkage estimators (Lasso) (62J07)
Related Items (3)
Cites Work
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- Penalized methods for bi-level variable selection
- Regularized estimation in sparse high-dimensional time series models
- The solution path of the generalized lasso
- Block length selection in the bootstrap for time series
- Autoregressive models for gene regulatory network inference: sparsity, stability and causality issues
- Biconvex sets and optimization with biconvex functions: a survey and extensions
- Joint estimation of multiple graphical models
- A group bridge approach for variable selection
- Minimization of a Non-Separable Objective Function Subject to Disjoint Constraints
- Stability Selection
- Bootstrap Methods for Time Series
- The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
- Model Selection and Estimation in Regression with Grouped Variables
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