Description Usage Arguments Value Author(s) References See Also Examples

Get the ratio cut and normalised cut values for the estimators along the path. It is part of the function in `fpca`

, the main part of this function is `single.cut`

.

1 | ```
fpca.cut(A, obj, fpca.cluster, K = 2, iso.seq)
``` |

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

`obj` |
a |

`fpca.cluster` |
a list of vectors, with each vector as 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. |

`iso.seq` |
a vector of the indices of those isolated nodes in the graph. If it is missing, |

`ratio.list` |
a list of ratio cut values for the estimator path. |

`normalised.list` |
a list of normalised cut values for the estimator path. |

Yang Feng, Richard J. Samworth and Yi Yu

Yang Feng, Richard J. Samworth and Yi Yu, Community Detection via Fused Principal Component Analysis, manuscript. Holland, P.W., Laskey, K.B. and Leinhardt, S., 1983. Stochastic block models: first steps. Social Networks 5, 109-137. Jin, J., 2012. Fast community detection by score. Karrer, B. and Newman, M.E.J., 2011. Stochastic blockmodels and community structure in networks. Physical Review E 83, 016107.

1 | ```
### please see the examples in fpca
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.