The following pages link to (Q5148950):
Displaying 12 items.
- Hierarchical sparse modeling: a choice of two group Lasso formulations (Q1704702) (← links)
- Confidence intervals for parameters in high-dimensional sparse vector autoregression (Q2076143) (← links)
- High-dimensional Linear Regression for Dependent Data with Applications to Nowcasting (Q4986331) (← links)
- Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions (Q5057240) (← links)
- High-Dimensional Vector Autoregressive Time Series Modeling via Tensor Decomposition (Q5881139) (← links)
- The EAS approach for graphical selection consistency in vector autoregression models (Q6059467) (← links)
- Regularized Estimation in High-Dimensional Vector Auto-Regressive Models Using Spatio-Temporal Information (Q6069868) (← links)
- Collective Anomaly Detection in High-Dimensional Var Models (Q6069887) (← links)
- Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages (Q6107231) (← links)
- Explainable AI for operational research: a defining framework, methods, applications, and a research agenda (Q6572853) (← links)
- FNETS: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series (Q6626256) (← links)
- Penalized Estimation of Sparse Markov Regime-Switching Vector Auto-Regressive Models (Q6631165) (← links)
