# Modularity based on DCBM and SBM assumptions

### Description

Get the modularity values based on DCBM and SBM assumptions for a single community detection estimator.

### Usage

1 | ```
single.mod(A, clusters, K = 2)
``` |

### Arguments

`A` |
input matrix – adjacency matrix of an observed graph based on the non-isolated nodes, of dimension |

`clusters` |
input vector – the estimator of the community labels of the non-isolated nodes in the network, of dimension |

`K` |
the number of the communities, with 2 as the default value. |

### Value

`mod.dcbm` |
the modularity value based on the DCBM assumption. |

`mod.sbm` |
the modularity value based on the SBM assumption. |

### Author(s)

Yang Feng, Richard J. Samworth and Yi Yu

### References

Yang Feng, Richard J. Samworth and Yi Yu, Community Detection via Fused Principal Component Analysis, manuscript.

### Examples

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