Description Usage Arguments Value Examples

lr.test allows to test between two nested ghype models whether there is enough evidence for the alternative (more complex) model compared to the null model.

1 2 3 4 5 6 7 8 9 10 11 |

`nullmodel` |
ghype object. The null model |

`altmodel` |
ghype object. The alternative model |

`df` |
optional scalar. the number of degrees of freedom. |

`Beta` |
boolean, whether to use empirical Beta distribution approximation. Default TRUE |

`seed` |
scalar, seed for the empirical distribution. |

`nempirical` |
optional scalar, number of replicates for empirical beta distribution. |

`parallel` |
optional, number of cores to use or boolean for parallel computation. If passed TRUE uses all cores-1, else uses the number of cores passed. If none passed performed not in parallel. |

`returnBeta` |
boolean, return estimated parameters of Beta distribution? Default FALSE. |

`method` |
string, for internal use |

p-value of test. If returnBeta=TRUE returns the p-value together with the parameters of the beta distribution.

1 2 3 4 | ```
data("adj_karate")
regularmodel <- regularm(graph = adj_karate, directed = FALSE, selfloops = FALSE)
confmodel <- scm(graph = adj_karate, directed = FALSE, selfloops = FALSE)
lr.test(nullmodel = regularmodel, altmodel = confmodel, seed = 123)
``` |

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