Creates mixture density plots. For each variable, a Total density plot will be shown, along with separate density plots for each latent class, where cases are weighted by the posterior probability of being assigned to that class.
plot_density(
x,
variables = NULL,
bw = FALSE,
conditional = FALSE,
alpha = 0.2,
facet_labels = NULL
)
Object for which a method exists.
Which variables to plot. If NULL, plots all variables that are present in all models.
Logical. Whether to make a black and white plot (for print) or a color plot. Defaults to FALSE, because these density plots are hard to read in black and white.
Logical. Whether to show a conditional density plot (surface area is divided among the latent classes), or a classic density plot (surface area of the total density plot is equal to one, and is divided among the classes).
Numeric (0-1). Only used when bw and conditional are FALSE. Sets the transparency of geom_density, so that classes with a small number of cases remain visible.
Named character vector, the names of which should
correspond to the facet labels one wishes to rename, and the values of which
provide new names for these facets. For example, to rename variables, in the
example with the 'iris' data below, one could specify:
facet_labels = c("Pet_leng" = "Petal length")
.
An object of class 'ggplot'.
if (FALSE) {
dat <-
iris[, c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width")]
names(dat) <- paste0("x", 1:4)
res <- mx_profiles(dat, 1:3)
plot_density(res)
}