hit_generator_from_multinomial: Under Const

In BayesianFROC: FROC Analysis by Bayesian Approaches

Description

Under Const

Usage

hit_generator_from_multinomial(
  z.truth = c(0.1, 0.2, 0.3, 0.4, 0.5),
  mu.truth = 1,
  v.truth = 2
)

Arguments

z.truth	Vector of dimension = C represents the thresholds of bi-normal assumption.
mu.truth	array of dimension (M,Q). Mean of the signal distribution of bi-normal assumption.
v.truth	array of dimension (M,Q). Standard Deviation of represents the signal distribution of bi-normal assumption.

Details

The algorithm of rmultinom() explained in ?rmultinom is quite same as mine code. So, I do not need to write this code. OK.

Value

A vector of non-negative integers

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