Plot density + ROC based on stats::_ — plot_density_ROC

Given positive and negative distribution NAMES and their arguments, plot the corresponding densities and their ROC-curves.

Usage

plot_density_ROC_str(
  dist_positive_str = "norm",
  dist_negative = "norm",
  dist_positive_args = list(mean = 0, sd = 1),
  dist_negative_args = list(mean = 0, sd = 1),
  length.out = 500,
  xmin = -3,
  xmax = 3
)

Arguments

dist_positive_str: A name of any distribution of the stats:: package. E.g. "norm", "binom", "exp". This is the distribution of values coming from the "positive"-class. For all possible distributions check ?stats::Distributions
dist_negative: A name of any distribution of the stats:: package. E.g. "norm", "binom", "exp". This is the distribution of values coming from the "negative"-class. For all possible distributions check ?stats::Distributions
dist_positive_args: Arguments to dist_positive_str as named list.
dist_negative_args: Arguments to dist_negative_str as named list.
length.out: The number of simulated points for the plots from the distributions. length.out points will be generated between [xmin, xmax]. PURELY VISUAL, ROC curves are calculated based on the actual distributions!
xmin: Minimum value of simulated points for the plots from the distributions. length.out points will be generated between [xmin, xmax]. PURELY VISUAL, ROC curves are calculated based on the actual distributions!
xmax: Maximum value of simulated points for the plots from the distributions. length.out points will be generated between [xmin, xmax]. PURELY VISUAL, ROC curves are calculated based on the actual distributions!

Value

patchwork'ed ggplots: left density, right ROC curve.

Examples


plot_density_ROC_str(length.out = 50)
#> $plot

#> 
#> $auc
#> 0.5 with absolute error < 5.6e-15
#> 
plot_density_ROC_str(
    dist_positive_str = "norm",
    dist_negative = "norm",
    dist_positive_args = list("mean" = 0, "sd" = 1),
    dist_negative_args = list("mean" = 1, "sd" = 1),
    xmin = -4, xmax = 7,
    length.out = 50
)
#> $plot

#> 
#> $auc
#> 0.23975 with absolute error < 4.9e-05
#> 
# pdf("removeme.pdf", width = 14, height = 6)
plot_density_ROC_str(
    dist_positive_str = "norm",
    dist_negative = "norm",
    dist_positive_args = list("mean" = 1, "sd" = 1),
    dist_negative_args = list("mean" = 0, "sd" = 1),
    xmin = -4, xmax = 7,
    length.out = 50
)
#> $plot

#> 
#> $auc
#> 0.76025 with absolute error < 4.9e-05
#> 
# dev.off()
# pdf("removeme_2.pdf", width = 14, height = 6)
plot_density_ROC_str(
    dist_positive_str = "norm",
    dist_negative = "norm",
    dist_positive_args = list("mean" = 1, "sd" = .5),
    dist_negative_args = list("mean" = 1, "sd" = 1),
    xmin = -4, xmax = 7,
    length.out = 50
)
#> $plot

#> 
#> $auc
#> 0.5 with absolute error < 5.6e-15
#> 
# dev.off()
# pdf("removeme_3.pdf", width = 14, height = 6)
plot_density_ROC_str(
    dist_positive_str = "norm",
    dist_negative = "norm",
    dist_positive_args = list("mean" = 1, "sd" = 2),
    dist_negative_args = list("mean" = 1, "sd" = 1),
    xmin = -4, xmax = 7,
    length.out = 50
)
#> $plot

#> 
#> $auc
#> 0.5 with absolute error < 5.6e-15
#> 
# dev.off()
tmp <- plot_density_ROC_str(
    dist_positive_str = "norm",
    dist_negative = "norm",
    dist_positive_args = list("mean" = 1, "sd" = 2),
    dist_negative_args = list("mean" = 1, "sd" = 1),
    xmin = -4, xmax = 7,
    length.out = 50
)