# lr.test

##### Perform likelihood ratio test between two ghype models.

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

```
# NOT RUN {
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)
# }
```

*Documentation reproduced from package ghypernet, version 1.0.0, License: AGPL-3*