Fig. 6
From: Jacobian Granger causality for count and binary data with applications to causal network inference
Comparison of the different JGC loss functions, AGC, and HMML on simulated neural spike train data (section) at different time series lengths T: (a) F-score, (b) adjusted sensitivity, (c) false discovery rate (FDR), (d) false negative rate (FNR). The adjusted sensitivity is computed as a ratio of the number of correctly identified interaction signs among the inferred edges that exist in the ground truth. As we are unable to extract interaction sign from HMML, it is excluded from (b). The exact numbers are given in the Supplementary Material.
