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BootstrapProperty()
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BootstrapProperty computes igraph analytics function on ensemble |
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CreateIgGraphs()
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Convert a list of adjacency matrices to a list of igraph graphs. |
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FitOmega()
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Fit propensity matrix for full model |
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JnBlock()
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Fisher Information matrix for estimators in block models. |
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RMSE()
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Computes the Root Mean Squared Error |
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RMSLE()
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Computes the Root Mean Squared Logged Error |
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adj2el()
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Maps adjacency matrix to edgelist |
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adj_karate
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Zachary's Karate Club graph |
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as.ghype()
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Map list to ghype object |
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bccm() print(<bccm>)
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Fitting bccm models |
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checkGraphtype()
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Check graph input type (for whether it's a graph or a edgelist). |
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coef(<nrm>)
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Extraction method for coefficients of models of class 'nrm'. |
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compute_xi() ComputeXi()
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Auxiliary function. Computes combinatorial matrix. |
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conf.test()
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Test regular (gnp) vs configuration model |
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highschool.predictors
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Highschool contact network adjacency matrix |
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cospons_mat
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Swiss MPs network adjacency matrix |
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coxsnellR2()
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Computes Cox and Snell pseudo R-squared for nrm models. |
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create_predictors() createPredictors()
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Create a nrmpredictor object from passed argument |
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create_predictors(<list>)
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Create a nrmpredictor object from list |
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dt
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Swiss MPs attribute data frame. |
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dtcommittee
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Swiss MPs committee affiliation data frame. |
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el2adj()
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Maps edgelist to adjacency matrix |
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extract.nrm.cluster()
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Extract details from statistical models for table construction. The function has methods for a range of statistical models. |
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get_zero_dummy()
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Create a dummy variable to encode zero values of another variable. |
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ghype() print(<ghype>)
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Fitting gHypEG models |
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gof.test()
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Perform a goodness-of-fit test |
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highschool.multiplex
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Highschool contact network multiplex representation |
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highschool.predictors
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Highschool contact network predictors |
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homophily_stat()
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Calculate homophily in multi-edge graphs. |
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isNetwork()
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Test null model vs full ghype. |
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linkSignificance() link_significance()
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Estimate statistical deviations from ghype model |
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logLik(<ghype>)
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Extract Log-Likelihood |
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logl()
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General method to compute log-likelihood for ghype models. |
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loglratio()
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Compute log-likelihood ratio for ghype models. |
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lr.test()
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Perform likelihood ratio test between two ghype models. |
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mat2vec.ix()
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Auxiliary function, gives mask for matrix for directed,
undirected etc. |
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mcfaddenR2()
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Computes Mc Fadden pseudo R-squared. |
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nr.ci()
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Confidence intervals for nrm models. |
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nr.significance()
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Computes the significance of more complex model against a simpler model by
means of a likelihood ratio test. |
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nrm() print(<nrm>)
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Fitting gHypEG regression models for multi-edge networks. |
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nrmChoose() nrm_choose()
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Selects the best set of predictors among the given sets by means of AIC. |
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nrmSelection() nrm_selection() print(<nrm_selection>)
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Perform AIC forward selection for nrm. |
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onlinesim_mat
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Swiss MPs committee similarity matrix. |
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predict(<nrm>)
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Method to predict the expected values of a nrm model |
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reciprocity_stat()
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Calculate weighted reciprocity change statistics for multi-edge graphs. |
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regularm()
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Fit the gnm model |
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residuals(<nrm>)
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Method to compute residuals of nrm models |
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rghype()
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Generate random realisations from ghype model. |
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scm()
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Fit the Soft-Configuration Model |
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sharedPartner_stat()
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Calculate (un-)weighted shared partner change statistics for multi-edge graphs. |
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summary(<nrm>) print(<summary.nrm>)
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Summary method for elements of class 'nrm'. |
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summary(<nrm_selection>) print(<summary.nrm_selection>)
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Summary method for elements of class 'nrm_selection'. |
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vec2mat()
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Auxiliary function, produces matrix from vector |
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vertexlabels
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Zachary's Karate Club vertex faction assignment |