All functions

BootstrapProperty()

BootstrapProperty computes igraph analytics function on ensemble

ComputeXi()

Auxiliary function. Computes combinatorial matrix.

CreateIgGraphs()

Convert a list of adjacency matrices to a list of igraph graphs.

FitOmega()

Fit propensity matrix for full model

JnBlock()

Fisher Information matrix for estimators in block models.

RMSE()

Computes the Root Mean Squared Error

RMSLE()

Computes the Root Mean Squared Logged Error

adj2el()

Maps adjacency matrix to edgelist

adj_karate

Zachary's Karate Club graph

as.ghype()

Map list to ghype object

bccm() print(<bccm>)

Fitting bccm models

checkGraphtype()

Check graph input type (for whether it's a graph or a edgelist).

coef(<nrm>)

Extraction method for coefficients of models of class 'nrm'.

conf.test()

Test regular (gnp) vs configuration model

highschool.predictors

Highschool contact network adjacency matrix

cospons_mat

Swiss MPs network adjacency matrix

coxsnellR2()

Computes Cox and Snell pseudo R-squared for nrm models.

create_predictors() createPredictors()

Create a nrmpredictor object from passed argument

create_predictors(<list>)

Create a nrmpredictor object from list

dt

Swiss MPs attribute data frame.

dtcommittee

Swiss MPs committee affiliation data frame.

el2adj()

Maps edgelist to adjacency matrix

extract.nrm.cluster()

Extract details from statistical models for table construction. The function has methods for a range of statistical models.

ghype() print(<ghype>)

Fitting gHypEG models

gof.test()

Perform a goodness-of-fit test

highschool.multiplex

Highschool contact network multiplex representation

highschool.predictors

Highschool contact network predictors

homophily_stat()

Calculate homophily in multi-edge graphs.

isNetwork()

Test null model vs full ghype.

linkSignificance()

Estimate statistical deviations from ghype model

logLik(<ghype>)

Extract Log-Likelihood

logl()

General method to compute log-likelihood for ghype models.

loglratio()

Compute log-likelihood ratio for ghype models.

lr.test()

Perform likelihood ratio test between two ghype models.

mat2vec.ix()

Auxiliary function, gives mask for matrix for directed, undirected etc.

mcfaddenR2()

Computes Mc Fadden pseudo R-squared.

nr.ci()

Confidence intervals for nrm models.

nr.significance()

Computes the significance of more complex model against a simpler model by means of a likelihood ratio test.

nrm() print(<nrm>)

Fitting gHypEG regression models for multi-edge networks.

nrmChoose() nrm_choose()

Selects the best set of predictors among the given sets by means of AIC.

nrmSelection() nrm_selection() print(<nrm_selection>)

Perform AIC forward selection for nrm.

onlinesim_mat

Swiss MPs committee similarity matrix.

predict(<nrm>)

Method to predict the expected values of a nrm model

reciprocity_stat()

Calculate weighted reciprocity change statistics for multi-edge graphs.

regularm()

Fit the gnm model

residuals(<nrm>)

Method to compute residuals of nrm models

rghype()

Generate random realisations from ghype model.

scm()

Fit the Soft-Configuration Model

sharedPartner_stat()

Calculate (un-)weighted shared partner change statistics for multi-edge graphs.

summary(<nrm>) print(<summary.nrm>)

Summary method for elements of class 'nrm'.

summary(<nrm_selection>) print(<summary.nrm_selection>)

Summary method for elements of class 'nrm_selection'.

vec2mat()

Auxiliary function, produces matrix from vector

vertexlabels

Zachary's Karate Club vertex faction assignment