Plot multiple (usually >2) distributions

Usage

plot_distributions_multiple(df_melted, ...)

Arguments

df_melted

A melted data.frame/tibble of values (x) and distribution names (Distribution)

E.g.: # A tibble: 1,000 × 2 x Distribution 1 0.974 A 2 0.196 A 3 -0.125 A 4 0.701 B 5 1.701 B 6 0.311 B

...

Further UNUSED parameters to be compliant to plot_distributions_2

Value

ggplot object with filled densities

Examples

sim_samples <- sim(
    list(
        "dist_1" = function(x) rnorm(x, mean = 1, sd = 1),
        "dist_2" = function(x) rnorm(x, mean = 0, sd = 1)
    ),
    do_melt = FALSE
)

density_estimates <- lapply(sim_samples, density, n = 100)
eval_seq <- seq(from = -5, to = 1, length.out = 250)
density_approximations <- tibble::as_tibble(vapply(density_estimates, function(densX) {
    stats::approx(densX[["x"]], densX[["y"]], eval_seq)[["y"]]
}, numeric(length(eval_seq))))
density_approximations[["x"]] <- eval_seq
density_approximations_long <- tidyr::pivot_longer(
    density_approximations,
    cols = names(density_approximations)[names(density_approximations) != "x"],
    names_to = "Distribution",
    values_to = "Probability density"
)

restrictedROC:::plot_distributions_multiple(density_approximations_long)