NSBM.Gen | R Documentation |

Generates networks from nomination stochastic block model for community structure in edge nomination procedures, proposed in Li et. al. (2020)

```
NSBM.Gen( n, K, avg.d,beta,theta.low=0.1,
theta.p=0.2,lambda.scale=0.2,lambda.exp=FALSE)
```

`n` |
size of network |

`K` |
number of communities |

`avg.d` |
expected average degree of the resuling network (after edge nomination) |

`beta` |
the out-in ratio of the original SBM |

`theta.low` |
the lower value of theta's. The theta's are generated as two-point mass at theta.low and 1. |

`theta.p` |
proportion of lower value of theta's |

`lambda.scale` |
standard deviation of the lambda (before the exponential, see lambda.exp) |

`lambda.exp` |
If TRUE, lambda is generated as exponential of uniformation random randomes. Otherwise, they are normally distributed. |

A list of

`A` |
the generated network adjacency matrix |

`g ` |
community membership |

`P ` |
probability matrix of the orignal SBM network |

`P.tilde ` |
probability matrix of the observed network after nomination |

`B ` |
B parameter |

`lambda ` |
lambda parameter |

`theta ` |
theta parameter |

Tianxi Li, Elizaveta Levina, Ji Zhu

Maintainer: Tianxi Li tianxili@virginia.edu

T. Li, E. Levina, and J. Zhu. Community models for networks observed through edge nominations. arXiv preprint arXiv:2008.03652 (2020).

```
dt <- NSBM.Gen(n=200,K=2,beta=0.2,avg.d=10)
```

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