plotROC {puma} | R Documentation |
Plots a Receiver Operator Characteristic (ROC) curve.
plotROC( scoresList , truthValues , includedProbesets=1:length(truthValues) , legendTitles=1:length(scoresList) , main = "PUMA ROC plot" , lty = 1:length(scoresList) , col = rep(1,length(scoresList)) , lwd = rep(1,length(scoresList)) , yaxisStat = "tpr" , xaxisStat = "fpr" , downsampling = 100 , showLegend = TRUE , showAUC = TRUE , ... )
scoresList |
A list, each element of which is a numeric vector of scores. |
truthValues |
A boolean vector indicating which scores are True Positives. |
includedProbesets |
A vector of indices indicating which scores (and truthValues) are to be used in the calculation. The default is to use all, but a subset can be used if, for example, you only want a subset of the probesets which are not True Positives to be treated as False Positives. |
legendTitles |
Vector of names to appear in legend. |
main |
Main plot title |
lty |
Line types. |
col |
Colours. |
lwd |
Line widths. |
yaxisStat |
Character string identifying what is to be plotted on the y-axis. The default is "tpr" for True Positive Rate. See performance function from ROCR package. |
xaxisStat |
Character string identifying what is to be plotted on the x-axis. The default is "fpr" for False Positive Rate. See performance function from ROCR package. |
downsampling |
See details for plot.performance from the ROCR package. |
showLegend |
Boolean. Should legend be displayed? |
showAUC |
Boolean. Should AUC values be included in legend? |
... |
Other parameters to be passed to plot . |
This function has no return value. The output is the plot created.
Richard D. Pearson
Related method calcAUC
class1a <- rnorm(1000,0.2,0.1) class2a <- rnorm(1000,0.6,0.2) class1b <- rnorm(1000,0.3,0.1) class2b <- rnorm(1000,0.5,0.2) scores_a <- c(class1a, class2a) scores_b <- c(class1b, class2b) scores <- list(scores_a, scores_b) classElts <- c(rep(FALSE,1000), rep(TRUE,1000)) plotROC(scores, classElts)