lr.test {ghypernet} | R Documentation |
Perform likelihood ratio test between two ghype models.
Description
lr.test allows to test between two nested ghype models whether there is enough evidence for the alternative (more complex) model compared to the null model.
Usage
lr.test(
nullmodel,
altmodel,
df = NULL,
Beta = TRUE,
seed = NULL,
nempirical = NULL,
parallel = FALSE,
returnBeta = FALSE,
method = NULL
)
Arguments
nullmodel |
ghype object. The null model |
altmodel |
ghype object. The alternative model |
df |
optional scalar. the number of degrees of freedom. |
Beta |
boolean, whether to use empirical Beta distribution approximation. Default TRUE |
seed |
scalar, seed for the empirical distribution. |
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. |
method |
string, for internal use |
Value
p-value of test. If returnBeta=TRUE returns the p-value together with the parameters of the beta distribution.
Examples
data("adj_karate")
regularmodel <- regularm(graph = adj_karate, directed = FALSE, selfloops = FALSE)
confmodel <- scm(graph = adj_karate, directed = FALSE, selfloops = FALSE)
lr.test(nullmodel = regularmodel, altmodel = confmodel, seed = 123)