Quantile-adaptive distributional Granger causal model for high-dimensional time series
A quantile-adaptive distributional Granger causal model (QA-DGCM) is developed to infer non-causal paths via an m-stage hypothesis testings based on distributional Granger causal effect (DGCE) statistic, which yields unique neurobiological insights advancing whole-brain effective connectivity analysis.