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 ggplot2::ggplot object

...

Not used (S3 compatibility).

Value

a ggplot2::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")
} # }