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Expected Influence (two-step)

Source: R/centrality.R
centrality_expected_influence_2.Rd

Two-step signed-weight sum: a node's own expected influence (EI1) plus the weighted sum of its neighbors' EI1 (Robinaugh, Millner & McNally 2016). Captures both the node's direct influence and the influence it exerts indirectly via highly-connected neighbors.

Usage

centrality_expected_influence_2(x, mode = "out", ...)

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.

Value

Named numeric vector of two-step expected-influence values.

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_1 for the one-step variant.

Examples

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_2(W)
#>    A    B    C    D 
#> 0.73 1.21 1.32 1.12