rocsurf.trin | R Documentation |
Function for computation of the trinormal ROC surface.
rocsurf.trin(x, y, z, p = 300, plot = TRUE, saveVUS = FALSE)
x, y, z |
Vectors containing the data of the three classes "healthy", "intermediate" and "diseased". |
p |
An integer for the precision of the surface. |
plot |
logical. If TRUE (default), the VUS is plotted using |
saveVUS |
A logical whether to save a PNG of the VUS in your current
working directory (default is |
This function takes three-class ROC data and computes the three
dimentional surface using the R-package rgl
. The ROC surface is
defined as
z = ROCs(t_-,t_+) = F_0(c_+) - F_0(c_-)=F_0(G_+^{-1}(t_+) ) -F_0(F_-^{-1}(t_-) ),
where c_-, c_+ are the two cut-off points and F_-, F_0, F_+ the cdf of the three classes with G = 1-F.
A list with the following components:
t1, t2 |
The vectors t_-=F_-^{(c_-)} and t_+=F_+^{(c_+)} |
zVUS |
The matix containing the surface values. |
x, y, z |
The original data. |
Xiong, C., G. Van Belle, et al. (2006). Measuring and estimating diagnostic accuracy when there are three ordinal diagnostic groups. Statistics in Medicine 25(7), 1251–1273.
data(cancer) x1 <- with(cancer, cancer[trueClass=="healthy", 8]) y1 <- with(cancer, cancer[trueClass=="intermediate", 8]) z1 <- with(cancer, cancer[trueClass=="diseased", 8]) rocsurf.trin(x1, y1, z1)
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