plot_ROC_empirical_curves: Empirical ROC curve

In BayesianFROC: FROC Analysis by Bayesian Approaches

Description

Empirical ROC curve

Usage

plot_ROC_empirical_curves(
  Number_of_cases = 100,
  Number_of_non_cases = 100,
  frequencies_of_non_cases = stats::rmultinom(1, size = Number_of_cases, prob = c(0.1,
    0.2, 0.3, 0.5)),
  frequencies_of_cases = stats::rmultinom(1, size = Number_of_non_cases, prob = c(0.4,
    0.3, 0.2, 0.1)),
  new.imaging.device = FALSE
)

Arguments

Number_of_cases	Number_of_cases
Number_of_non_cases	Number_of_non_cases
frequencies_of_non_cases	frequencies_of_non_cases
frequencies_of_cases	frequencies_of_cases
new.imaging.device	Logical: TRUE of FALSE. If TRUE (default), then open a new device to draw curve. Using this we can draw curves in same plain by new.imaging.device=FALSE.

Details

Suppose that there is a K categories and data are drawn from two multinomial distributions of size n,m.

h_1,h_2,...,h_K, Σ h_i = n,

f_1,f_2,...,f_K,Σ f_i = m.

Then this plots the cumulative sums.

BayesianFROC documentation built on Jan. 23, 2022, 9:06 a.m.