Description Usage Arguments Value Note See Also Examples

`dCommSignif`

is supposed to test the significance of communities
within a graph. For a community of the graph, it first calculates two
types of degrees for each node: degrees based on parters only within
the community itself, and the degrees based on its parters NOT in the
community but in the graph. Then, it performs two-sample Wilcoxon tests
on these two types of degrees to produce the signficance level
(p-value)

1 | ```
dCommSignif(g, comm)
``` |

`g` |
an object of class "igraph" or "graphNEL" |

`comm` |
an object of class "communities". Details on this class can be found at http://igraph.org/r/doc/communities.html |

`significance`

: a vector of p-values (significance)

none

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
# 1) generate an vector consisting of random values from beta distribution
x <- rbeta(1000, shape1=0.5, shape2=1)
# 2) fit a p-value distribution under beta-uniform mixture model
fit <- dBUMfit(x, ntry=1, hist.bum=FALSE, contour.bum=FALSE)
# 3) calculate the scores according to the fitted BUM and fdr=0.01
# using "pdf" method
scores <- dBUMscore(fit, method="pdf", fdr=0.05, scatter.bum=FALSE)
names(scores) <- as.character(1:length(scores))
# 4) generate a random graph according to the ER model
g <- erdos.renyi.game(1000, 1/100)
# 5) produce the induced subgraph only based on the nodes in query
subg <- dNetInduce(g, V(g), knn=0)
# 6) find the module with the maximum score
module <- dNetFind(subg, scores)
# 7) find the module and test its signficance
comm <- walktrap.community(module, modularity=TRUE)
significance <- dCommSignif(module, comm)
``` |

```
Loading required package: igraph
Attaching package: 'igraph'
The following objects are masked from 'package:stats':
decompose, spectrum
The following object is masked from 'package:base':
union
Loading required package: supraHex
Loading required package: hexbin
A total of p-values: 1000
Maximum Log-Likelihood: 328.8
Mixture parameter (lambda): 0.000
Shape parameter (a): 0.489
```

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