Display the criteria associated with a collection of PLNPCA fits (a PLNPCAfamily)

```
# S3 method for PLNPCAfamily
plot(x, criteria = c("loglik", "BIC", "ICL"), reverse = FALSE, ...)
```

## Arguments

- x
an R6 object with class `PLNPCAfamily`

- criteria
vector of characters. The criteria to plot in c("loglik", "BIC", "ICL").
Default is c("loglik", "BIC", "ICL").

- reverse
A logical indicating whether to plot the value of the criteria in the "natural" direction
(loglik - 0.5 penalty) or in the "reverse" direction (-2 loglik + penalty). Default to FALSE, i.e use the
natural direction, on the same scale as the log-likelihood.

- ...
additional parameters for S3 compatibility. Not used

## Value

Produces a plot representing the evolution of the criteria of the different models considered,
highlighting the best model in terms of BIC and ICL (see details).

## Details

The BIC and ICL criteria have the form 'loglik - 1/2 * penalty'
so that they are on the same scale as the model log-likelihood. You can change this direction and use the alternate form '-2*loglik + penalty', as some authors do, by setting `reverse = TRUE`

.

## Examples

```
data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
myPCAs <- PLNPCA(Abundance ~ 1 + offset(log(Offset)), data = trichoptera, ranks = 1:5)
#>
#> Initialization...
#>
#> Adjusting 5 PLN models for PCA analysis.
#> Rank approximation = 1
Rank approximation = 5
Rank approximation = 2
Rank approximation = 4
Rank approximation = 3
#> Post-treatments
#> DONE!
if (FALSE) {
plot(myPCAs)
}
```