causal_emergence {einet} | R Documentation |
Given a microscale network, G
, this function iteratively checks different
coarse-grainings to see if it finds one with higher effective information.
causal_emergence(x, ...)
x |
igraph or matrix object. |
... |
Span, and threshold parameters |
A list with letters and numbers.
g_micro - Graph of original micro-scale network.
g_macro - Graph of macro-scale network.
mapping - list
mapping from micro to macro scales giving
the largest increase in effective information.
ei_macro - Effective information of macro scale network.
ei_micro - Effective information of micro scale network.
ce - Numerical value for causal emergence.
graph <- matrix(
cbind(
c(0.0, 1.0, 0.0, 0.0),
c(0.0, 0.0, 1.0, 0.0),
c(0.0, 0.0, 0.0, 1.0),
c(0.0, 0.0, 0.0, 0.0)
),
nrow = 4
) %>%
igraph::graph.adjacency(mode = "directed")
causal_emergence(graph)