cograph (version 2.7.2)

centrality_expected_influence_1: Expected Influence (one-step)

Description

Signed-weight sum of a node's edges (Robinaugh, Millner & McNally 2016). The appropriate centrality for networks with positive and negative edges (partial-correlation, glasso, signed correlation networks) where treating negative edges as positive magnitudes can be misleading.

Usage

centrality_expected_influence_1(x, mode = "out", ...)

Value

Named numeric vector of expected-influence values (signed).

Arguments

x

Network input (matrix, igraph, network, cograph_network, tna object).

mode

One of "all", "in", "out" for directed graphs. Default "out".

...

Additional arguments passed to centrality.

References

Robinaugh DJ, Millner AJ, McNally RJ (2016). Identifying highly influential nodes in the complicated grief network. Journal of Abnormal Psychology, 125(6), 747-757.

See Also

centrality_expected_influence_2 for the two-step variant, centrality_strength for the weighted-degree analogue.

Examples

# Signed weight matrix (partial correlations, for example)
W <- matrix(c( 0.0,  0.5, -0.3,  0.2,
               0.5,  0.0,  0.4, -0.1,
              -0.3,  0.4,  0.0,  0.6,
               0.2, -0.1,  0.6,  0.0), 4, 4, byrow = TRUE)
rownames(W) <- colnames(W) <- c("A", "B", "C", "D")
centrality_expected_influence_1(W)