Represent the result of the clustering either by coloring the individual in a two-dimension PCA factor map, or by representing the expected matrix of count reorder according to the clustering.

# S3 method for class 'PLNmixturefit'
plot(x, type = c("pca", "matrix"), main = NULL, plot = TRUE, ...)

Arguments

x

an R6 object with class PLNmixturefit

type

character for the type of plot, either "pca", for or "matrix". Default is "pca".

main

character. A title for the plot. If NULL (the default), an hopefully appropriate title will be used.

plot

logical. Should the plot be displayed or sent back as ggplot object

...

Not used (S3 compatibility).

Value

a ggplot graphic

Examples

data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
myPLN <- PLNmixture(Abundance ~ 1 + offset(log(Offset)),
           data = trichoptera, control = PLNmixture_param(smoothing = "none"))  %>% getBestModel()
#> 
#>  Initialization...
#> 
#>  Adjusting 5 PLN mixture models.
#> 	number of cluster = 1 
	number of cluster = 2 
	number of cluster = 3 
	number of cluster = 4 
	number of cluster = 5 

#>  Post-treatments
#>  DONE!
if (FALSE) { # \dontrun{
plot(myPLN, "pca")
plot(myPLN, "matrix")
} # }