`logl.Rd`

General method to compute log-likelihood for ghype models.

logl( object, xi = NULL, omega = NULL, directed = NULL, selfloops = NULL, adj = NULL, multinomial = NULL, ... ) # S3 method for ghype logl( object, xi = NULL, omega = NULL, directed = NULL, selfloops = NULL, adj = NULL, multinomial = NULL, ... ) # S3 method for matrix logl( object, xi = NULL, omega = NULL, directed = NULL, selfloops = NULL, adj = NULL, multinomial = NULL, ... )

object | either an adjacency matrix or ghype model If a ghype model is passed, then `xi`, `omega`, `directed`, `selfloops` are ignored If an adjacency matrix is passed, then `adj` is ignored |
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xi | matrix, combinatorial matrix to build ghype model, considered only if object is an adjacency matrix |

omega | matrix, propensity matrix to build ghype model, considered only if object is an adjacency matrix |

directed | boolean, is ghype model directed? considered only if object is an adjacency matrix |

selfloops | boolean, has ghype model selfloops? considered only if object is an adjacency matrix |

adj | optional matrix, adjacency matrix of which to compute log-likelihood, cconsidered only if object is ghype model If adj is not passed, and object is a ghype model, the log-likelihood is computed for the original adjacency matrix stored in object. |

multinomial | optional boolean. Force multinomial approximation? If not chosen, multinomial chosen for large graphs. |

... | additional parameters passed to and from internal methods |

loglikelihood value

`ghype`

: Computes log-likelihood for ghype models from model object`matrix`

: Computes log-likelihood for ghype models from adjacency.

#> [1] -434.5449new_adj <- adj_karate new_adj[3,4] <- 10 logl(object=model, adj=new_adj)#> [1] -445.8136