rocdemo.sca {ROC} | R Documentation |
rocdemo.sca – demonstrate 'rocc' class construction using a scalar marker and simple functional rule
rocdemo.sca(truth, data, rule=NULL, cutpts=NA, markerLabel="unnamed marker", caseLabel="unnamed diagnosis")
truth |
true classification of objects. Must take values 0 or 1. |
data |
quantitative markers used to classify |
rule |
rule: a function with arguments (x, thresh) returning 0
or 1. If no rule is provided the standard rule dxrule.sca is
assumed and a faster implementation utilized. |
cutpts |
values of thresholds |
markerLabel |
textual label describing marker |
caseLabel |
textual label describing classification |
dxrule.sca is function (x, thresh) ifelse(x > thresh, 1, 0)
The default value of argument cutpts is a point less than min(data), points separating the unique values of data and a point greater than max(data).
an object of S4 class rocc
Vince Carey (stvjc@channing.harvard.edu)
AUC
set.seed(123) R1 <- rocdemo.sca( rbinom(40,1,.3), rnorm(40), caseLabel="new case", markerLabel="demo Marker" ) plot(R1, line=TRUE, show.thresh=TRUE) truth <- c(0, 1, 0, 1, 1, 0, 1, 1) data <- c(2, 3, 4, 4, 5, 6, 7, 8) R2 <- rocdemo.sca(truth, data, dxrule.sca) plot(R2, line=TRUE, show.thresh=TRUE) R3 <- rocdemo.sca(truth, data, function(x, thresh) 1 - dxrule.sca(x, thresh)) if (AUC(R2) + AUC(R3) != 1) stop('Sum of AUCs should be 1.')