clusteringCoefficient-methods {graph} | R Documentation

## Clustering coefficient of a graph

### Description

This generic function takes an object that inherits from the `graph` class. The graph needs to have `edgemode=="undirected"`. If it has `edgemode=="directed"`, the function will return NULL.

### Usage

    ## S4 method for signature 'graph'
    clusteringCoefficient(object, selfLoops=FALSE)

### Arguments

`object` | An instance of the appropriate graph class.
`selfLoops` | Logical. If true, the calculation takes self loops into account.

### Details

For a node with n adjacent nodes, if `selfLoops` is `FALSE`, the clustering coefficent is N/(n*(n-1)), where N is the number of edges between these nodes. The graph may not have self loops. If `selfLoops` is `TRUE`, the clustering coefficent is N/(n*n), where N is the number of edges between these nodes, including self loops.

### Value

A named numeric vector with the clustering coefficients for each node. For nodes with 2 or more edges, the values are between 0 and 1. For nodes that have no edges, the function returns the value NA. For nodes that have exactly one edge, the function returns NaN.

### Author(s)

Wolfgang Huber http://www.dkfz.de/mga/whuber

### Examples

    set.seed(123)
    g1 <- randomGraph(letters[1:10], 1:4, p=.3)
    clusteringCoefficient(g1)
    clusteringCoefficient(g1, selfLoops=TRUE)

[Package graph version 1.68.0 Index]