isNetwork tests a graph for the SCM vs the full ghype model.

isNetwork(
  graph,
  directed,
  selfloops,
  Beta = TRUE,
  nempirical = NULL,
  parallel = FALSE,
  returnBeta = FALSE,
  seed = NULL
)

Arguments

graph

adjacency matrix or igraph graph

directed

a boolean argument specifying whether object is directed or not.

selfloops

a boolean argument specifying whether the model should incorporate selfloops.

Beta

boolean, use Beta test? default TRUE

nempirical

optional, number of graphs to sample from null distribution for empirical 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.

seed

optional integer, seed for empirical lr.test

Value

p-value of test.

Examples

data("adj_karate") isNetwork(graph = adj_karate, directed = FALSE, selfloops = FALSE, seed=123)
#> #> LR test -- optimal = CM vs full model #> #> data: #> lr = 649.84, df = 560, p-value < 2.2e-16 #> alternative hypothesis: one.sided #> 95 percent confidence interval: #> 339.1651 413.9994 #>