id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_4i3v2eiupvdt5gqy5o2tdcvz2e	Aditi Kathpalia	Data-based intervention approach for Complexity-Causality measure	2019	24	.pdf	application/pdf	10465	1134	64	Data-based intervention approach for Complexity-Causality measure. Figure 4 Standard deviation of causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR(1) processes, from Y to X (solid line-circles, black) and X to Y (solid line-crosses, magenta) as Figure 5 Mean causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR(100) processes, from Y to X (solid line-circles, black) and X to Y (solid line-crosses, magenta) as the degree of Figure 5 Mean causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR(100) processes, from Y to X (solid line-circles, black) and X to Y (solid line-crosses, magenta) as the degree of Figure 8 Mean causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR processes Figure 8 Mean causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR processes	./cache/work_4i3v2eiupvdt5gqy5o2tdcvz2e.pdf	./txt/work_4i3v2eiupvdt5gqy5o2tdcvz2e.txt