Description Usage Arguments Value References Examples

View source: R/communicability_measures.R

The communicability of an adjacency matrix M is defined as exp(M) where
M[i,j] can be interpreted as the weighted sums of paths from i to j.
Recall that exp(M) can be cast into a Taylor series expansion with an
infinite number additive terms.
The function permits the evaluation of exp(M) using the `expm`

package
or using a simpler mathematical approximation.
In the second case, the function truncates the infinite series by
simply calculating the summation terms up to a pre-defined number of factors.

1 | ```
communicability_matrix(x, terms = Inf, sparse = TRUE)
``` |

`x` |
a square |

`terms` |
truncates the communicability matrix evaluation up to a pre-defined number of terms.
If |

`sparse` |
should the function use sparse matrices when computing the communicability?
However, if |

The function returns the communicability matrix.

Estrada, E. Hatano, N. (2008). Communicability in complex networks. Physical Review E, 77:036111.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
# Creating example data
## Assets Matrix (bilateral exposures)
assets_matrix <- matrix(c(0, 10, 3, 1, 0, 2, 0, 3, 0), ncol = 3)
rownames(assets_matrix) <- colnames(assets_matrix) <- letters[1:3]
## Capital Buffer
buffer <- c(a = 2, b = 5, c = 2)
# Computing vulnerability
v <- vulnerability_matrix(assets_matrix, buffer, binary = TRUE)
# Computing communicability of the vulnerability matrix
communicability_matrix(v)
``` |

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