The EAS approach for graphical selection consistency in vector autoregression models
The EAS approach for graphical selection consistency in vector autoregression models
Abstract As evidenced by various recent and significant papers within the frequentist literature, along with numerous applications in macroeconomics, genomics, and neuroscience, there continues to be substantial interest in understanding the theoretical estimation properties of high‐dimensional vector autoregression (VAR) models. To date, however, while Bayesian VAR (BVAR) models have been …