Strong selection consistency of Bayesian vector autoregressive models based on a pseudo-likelihood approach
基于伪似然的贝叶斯向量自回归模型强选择一致性
Vector autoregressive (VAR) models aim to capture linear temporal interdependencies among multiple time series. They have been widely used in macroeconomics and financial econometrics and more recently have found novel applications in functional genomics and neuroscience. These applications have also accentuated the need to investigate the behavior of the VAR model in a high-dimensional regime, which will provide novel insights into the role of temporal dependence for…