# plot.gsym.point: Default plotting of a gsym.point object In GsymPoint: Estimation of the Generalized Symmetry Point, an Optimal Cutpoint in Continuous Diagnostic Tests

## Description

On the basis of a `gsym.point` object, it is used to plot the Receiver Operating Characteristic (ROC) curve, the line y = 1-ρ t and the optimal ROC coordinates associated to the Generalized Symmetry point.

## Usage

 ```1 2 3``` ```## S3 method for class 'optimal.cutpoints' ## S3 method for class 'gsym.point' plot(x, xlab, ylab, main, ...) ```

## Arguments

 `x` an object of class `gsym.point` as produced by the `gsym.point()` function `xlab` the x axis label of the plot. By default this label is set to "False Positive Rate" `ylab` the y axis label of the plot. By default this label is set to "True Positive Rate" `main` the title of the plot. By default this title is set to "Empirical ROC Curve and line y = 1-ρ x" `...` further arguments passed to or from other methods

## Author(s)

M<f3>nica L<f3>pez-Rat<f3>n, Carmen Cadarso-Su<e1>rez, Elisa M. Molanes-L<f3>pez and Emilio Let<f3>n

`gsym.point`, `control.gsym.point`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42``` ```library(GsymPoint) data(melanoma) ########################################################### # Generalized Pivotal Quantity Method ("GPQ"): ########################################################### gsym.point.GPQ.melanoma<-gsym.point(methods = "GPQ", data = melanoma, marker = "X", status = "group", tag.healthy = 0, categorical.cov = NULL, CFN = 1, CFP = 1, control = control.gsym.point(),confidence.level = 0.95, trace = FALSE, seed = FALSE, value.seed = 3, verbose = FALSE) plot(gsym.point.GPQ.melanoma) data(prostate) ########################################################### # Generalized Pivotal Quantity Method ("GPQ"): ########################################################### gsym.point.GPQ.prostate <- gsym.point (methods = "GPQ", data = prostate, marker = "marker", status = "status", tag.healthy = 0, categorical.cov = NULL, CFN = 1, CFP = 1, control = control.gsym.point(), confidence.level = 0.95, trace = FALSE, seed = FALSE, value.seed = 3, verbose = FALSE) plot(gsym.point.GPQ.prostate) data(elastase) ########################################################### # Generalized Pivotal Quantity Method ("GPQ"): ########################################################### gsym.point.GPQ.elastase <- gsym.point(methods = "GPQ", data = elastase, marker = "elas", status = "status", tag.healthy = 0, categorical.cov = NULL, CFN = 1, CFP = 1, control = control.gsym.point(), confidence.level = 0.95, trace = FALSE, seed = FALSE, value.seed = 3, verbose = FALSE) plot(gsym.point.GPQ.elastase) ```