Perform a goodness-of-fit test

gof.test(
  model,
  Beta = TRUE,
  nempirical = NULL,
  parallel = NULL,
  returnBeta = FALSE,
  seed = NULL
)

Arguments

model

ghype model to test

Beta

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

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.

seed

scalar, seed for the empirical distribution.

Value

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

Examples

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