# plot: Plot an ROC curve object In nsROC: Non-Standard ROC Curve Analysis

## Description

This function plots a 'groc', 'rocbands' or 'cdroc' object.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```## S3 method for class 'groc' plot(x, lwd = 2, xlab = "False-Positive Rate", ylab = "True-Positive Rate", main = "ROC curve", ...) ## S3 method for class 'rocbands' plot(x, type='s', lwd=2, xlim=c(0,1), ylim=c(0,1), xlab="False-Positive Rate", ylab="True-Positive Rate", main=paste("ROC curve \n (", obj\$method, " confidence bands)", sep=""), col='aquamarine3', col.inside="azure2", col.frontier="azure3", lwd.frontier=2, ...) ## S3 method for class 'cdroc' plot(x, type='s', lwd=3, xlab='1 - Specificity', ylab='Sensitivity', xaxs='i', yaxs='i', main=paste("ROC curve at time", obj\$predict.time), ...) ```

## Arguments

 `x ` a 'groc', 'rocbands' or 'cdroc' object from the `gROC`, `ROCbands` or `cdROC` respectively. `type ` what type of plot should be drawn. `lwd ` the line width to be used for ROC curve estimate, a positive number. See `par`. `col ` the color to be used for ROC curve estimate. See `par`. `lwd.frontier ` the line width to be used for ROC curve confidence bands estimate. `col.inside, col.frontier ` the color to be used for ROC curve confidence bands estimate (`col.frontier`) and for the area inside (`col.inside`). `xlim, ylim ` numeric vectors of length 2, giving the x and y coordinates ranges. See `plot.window`. `xlab, ylab ` a title for the x and y axis, respectively. See `title`. `xaxs, yaxs ` the style of axis interval calculation to be used for the x and y axis, respectively. See `par`. `main ` an overall title for the plot. See `title`. `... ` further arguments to be passed to methods, such as graphical parameters. See `par`.

## Value

These functions return a plot of the object they were passed.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```# Data generation set.seed(123) X <- c(rnorm(45), rnorm(30,2,1.5)) D <- c(rep(0,45), rep(1,30)) # Plot an ROC curve grocobj <- gROC(X,D) plot(grocobj) # Plot ROC curve confidence bands rocbandsobj <- ROCbands(grocobj) plot(rocbandsobj) # Plot cumulative/dynamic ROC curve set.seed(123) stime <- rchisq(50,3) status <- sample(c(rep(1,40), rep(0,10))) marker <- max(stime) - stime + rnorm(50,0,2) cdrocobj <- cdROC(stime, status, marker, 2.8, ci=TRUE) plot(cdrocobj) ```

### Example output   ```
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nsROC documentation built on May 2, 2019, 2:31 p.m.