Description Usage Arguments Value References Examples

'graph.entropy' returns the spectral entropy of a given undirected graph.

1 | ```
graph.entropy(A = NULL, bandwidth = "Silverman", eigenvalues = NULL)
``` |

`A` |
the adjacency matrix of the graph. For an unweighted graph it contains only 0s and 1s. For a weighted graph, it may contain nonnegative real values that correspond to the weights of the edges. |

`bandwidth` |
string indicating which criterion will be used to choose the bandwidth during the spectral density estimation. The available criteria are "Silverman" (default) and "Sturges". |

`eigenvalues` |
optional parameter. It contains the eigenvalues of matrix A. Then, if the eigenvalues of matrix A have already been computed, this parameter can be used instead of A. If no value is passed, then the eigenvalues of A will be computed by 'graph.entropy'. |

a real number corresponding to the graph spectral entropy.

Takahashi, D. Y., Sato, J. R., Ferreira, C. E. and Fujita A. (2012) Discriminating Different Classes of Biological Networks by Analyzing the Graph Spectra Distribution. _PLoS ONE_, *7*, e49949. doi:10.1371/journal.pone.0049949.

Silverman, B. W. (1986) _Density Estimation_. London: Chapman and Hall.

Sturges, H. A. The Choice of a Class Interval. _J. Am. Statist. Assoc._, *21*, 65-66.

1 2 3 4 5 | ```
require(igraph)
G <- erdos.renyi.game(100, p=0.5)
A <- as.matrix(get.adjacency(G))
entropy <- graph.entropy(A)
entropy
``` |

statGraph documentation built on Jan. 11, 2019, 1:06 a.m.

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