Directed graphs and variable selection in large vector autoregressive models
From MaRDI portal
Publication:6135342
DOI10.1111/jtsa.12664OpenAlexW2759172196WikidataQ114079555 ScholiaQ114079555MaRDI QIDQ6135342
Unnamed Author, Christian Kascha, Ralf Brüggemann
Publication date: 24 August 2023
Published in: Journal of Time Series Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/jtsa.12664
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On asymptotically optimal confidence regions and tests for high-dimensional models
- Regularized estimation in sparse high-dimensional time series models
- Granger causality and path diagrams for multivariate time series
- Short run and long run causality in time series: inference
- Graphical modelling of multivariate time series
- Forecasting with factor-augmented regression: a frequentist model averaging approach
- Oracle inequalities for high dimensional vector autoregressions
- \(\ell_1\)-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors
- Real-time factor model forecasting and the effects of instability
- Least squares after model selection in high-dimensional sparse models
- Testing for high-dimensional network parameters in auto-regressive models
- Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
- An Implementation of Tarjan's Algorithm for the Block Triangularization of a Matrix
- Accounting for Lag Order Uncertainty in Autoregressions: the Endogenous Lag Order Bootstrap Algorithm
- Impulse Response Functions Based on a Causal Approach to Residual Orthogonalization in Vector Autoregressions
- Forecasting Using Principal Components From a Large Number of Predictors
- Introduction to Graphical Modelling
- Short Run and Long Run Causality in Time Series: Theory
- Graphs for Dependence and Causality in Multivariate Time Series
- Investigating Causal Relations by Econometric Models and Cross-spectral Methods
- Depth-First Search and Linear Graph Algorithms
- Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
- The bootstrap and Edgeworth expansion
- Graphical interaction models for multivariate time series.
This page was built for publication: Directed graphs and variable selection in large vector autoregressive models