gof.test.Rd
Perform a goodness-of-fit test
gof.test( model, Beta = TRUE, nempirical = NULL, parallel = NULL, returnBeta = FALSE, seed = NULL )
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. |
p-value of test. If returnBeta=TRUE returns the p-value together with the parameters of the beta distribution.
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 #>