Vector autoregression has been widely used for modeling and analysis of multivariate time series data. In high-dimensional settings, model parameter regularization schemes inducing sparsity yield interpretable models and achieved good forecasting …
The joint estimation of multiple graphical models from high-dimensional data has been studied in the statistics and machine learning literature, owing to its importance in diverse fields including molecular biology, neuroscience, and the social …