Integrated Classification Likelihood

Generic function to compute the Integrated Classification Likelihood (ICL) of a fitted model. ICL = BIC - entropy of the variational distribution (larger is better).

ICL.PLNfit: ICL for a fitted PLNfit.

ICL.ZIPLNfit: ICL for a fitted ZIPLNfit.

Usage

ICL(object, ...)

# S3 method for class 'PLNfit'
ICL(object, ...)

# S3 method for class 'ZIPLNfit'
ICL(object, ...)

Arguments

object: an R6 object with class ZIPLNfit
...: additional parameters passed to methods

Value

A scalar: the variational ICL (larger is better).

Examples

data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
model <- PLN(Abundance ~ 1, data = trichoptera)
#> 
#>  Initialization...
#>  Adjusting a full covariance PLN model with nlopt optimizer
#>  Post-treatments...
#>  DONE!
ICL(model)
#> [1] -2270.936
data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
#> Warning: ! There are no matching names in `counts` and `covariates`.
#> ℹ Function will proceed assuming:
#> ℹ - samples are in the same order;
#> ℹ - samples are rows of `counts`.
#> Error in prepare_data(trichoptera$Abundance, trichoptera$Covariate): ✖ `counts` and `covariates` have different number of row(s):
#> ℹ `counts` has <49> row(s);
#> ℹ `covariates` has <0> row(s).
model <- ZIPLN(Abundance ~ 1, data = trichoptera)
#> 
#>  Initialization...
#>  Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component.
#>  DONE!
ICL(model)
#> [1] -2365.88