View source: R/centrality-batch14.R
| centrality_dynamical_importance | R Documentation |
Restrepo, Ott & Hunt's node dynamical importance is the relative drop
in adjacency spectral radius on removing that node:
I_i = (\rho(A)-\rho(A_{-i}))/\rho(A) (equation 2).
This function recomputes the spectral radius after every deletion. The
paper's left/right eigenvector product (equation 5) is an approximation
and can differ substantially on small networks; it is not used here.
centrality_dynamical_importance(x, ...)
x |
Network input accepted by |
... |
Additional arguments to |
Supports directed or undirected nonnegative weighted networks. Self-loops
are always removed, as in the paper's zero-diagonal definition. Edge
weights, weighted and simplify follow the same adjacency
conventions as centrality_diffusion_centrality. The measure
is invariant to reversing all arcs and ignores mode and path-weight
inversion. Disconnected graphs use the spectral radius of the whole graph.
When the original spectral radius is zero (including any directed acyclic
graph), the ratio is undefined and all vertices receive NaN.
Isolates in a graph with positive spectral radius receive zero. The empty
graph returns an empty vector. Strong components are evaluated separately
so acyclic parts contribute exactly zero, avoiding numerical eigenvalues
of nilpotent blocks. Roundoff in the final ratio is clipped to zero or one.
Repeated eigendecomposition is costly. Select this measure explicitly or
use include = "dynamical_importance"; it is held back from the
default type = "all" tier.
Named numeric vector in input node order.
Restrepo, J. G., Ott, E., & Hunt, B. R. (2006). Characterizing the Dynamical Importance of Network Nodes and Links. Physical Review Letters, 97, 094102. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1103/PhysRevLett.97.094102")}.
centrality_dynamical_importance(igraph::make_full_graph(4))
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