Description Usage Arguments Value Author(s) References Examples

Computes global average shortest path length, local average shortest path length, eccentricity, and diameter of a network

1 | ```
pathlengths(A, weighted = FALSE)
``` |

`A` |
An adjacency matrix of network data |

`weighted` |
Is the network weighted? Defaults to FALSE. Set to TRUE for weighted measures |

Returns a list containing:

`ASPL` |
Global average shortest path length |

`ASPLi` |
Local average shortest path length |

`ecc` |
Eccentricity (i.e., maximal shortest path length between a node and any other node) |

`D` |
Diameter of the network (i.e., the maximum of eccentricity) |

Alexander Christensen <[email protected]>

Rubinov, M., & Sporns, O. (2010).
Complex network measures of brain connectivity: Uses and interpretations.
*Neuroimage*, *52*, 1059-1069.
doi: 10.1016/j.neuroimage.2009.10.003

1 2 3 4 5 6 7 | ```
A<-TMFG(neoOpen)$A
#Unweighted
PL <- pathlengths(A)
#Weighted
PL <- pathlengths(A, weighted = TRUE)
``` |

AlexChristensen/NetworkToolbox documentation built on Nov. 6, 2018, 2:54 a.m.

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