ROCPlotPair2 {WVPlots}

Compare two ROC plots.

Description

Plot two receiver operating characteristic curves from different data frames.

Usage

ROCPlotPair2(
  nm1,
  frame1,
  xvar1,
  truthVar1,
  truthTarget1,
  nm2,
  frame2,
  xvar2,
  truthVar2,
  truthTarget2,
  title,
  ...,
  estimate_sig = TRUE,
  returnScores = FALSE,
  nrep = 100,
  parallelCluster = NULL,
  palette = "Dark2"
)

Arguments

nm1

name of first model

frame1

data frame to get values from

xvar1

name of the first independent (input or model) column in frame

truthVar1

name of the dependent (output or result to be modeled) column in frame

truthTarget1

value we consider to be positive

nm2

name of second model

frame2

data frame to get values from

xvar2

name of the first independent (input or model) column in frame

truthVar2

name of the dependent (output or result to be modeled) column in frame

truthTarget2

value we consider to be positive

title

title to place on plot

...

no unnamed argument, added to force named binding of later arguments.

estimate_sig

logical, if TRUE estimate and display significance of difference from AUC 0.5.

returnScores

logical if TRUE return detailed permutedScores

nrep

number of permutation repetitions to estimate p values.

parallelCluster

(optional) a cluster object created by package parallel or package snow.

palette

name of Brewer palette to color curves (can be NULL)

Details

Use this curve to compare model predictions to true outcome from two data frames, each of which has its own model predictions and true outcome columns.

If palette is NULL, plot colors will be chosen from the default ggplot2 palette. Setting palette to NULL allows the user to choose a non-Brewer palette, for example with scale_color_manual.

See Also

ROCPlot

Examples

if (requireNamespace('data.table', quietly = TRUE)) {
	# don't multi-thread during CRAN checks
		data.table::setDTthreads(1)
}

set.seed(34903490)
x1 = rnorm(50)
x2 = rnorm(length(x1))
y = 0.2*x2^2 + 0.5*x2 + x1 + rnorm(length(x1))
frm = data.frame(x1=x1,x2=x2,yC=y>=as.numeric(quantile(y,probs=0.8)))
# WVPlots::ROCPlot(frm, "x1", "yC", TRUE, title="Example ROC plot")
# WVPlots::ROCPlot(frm, "x2", "yC", TRUE, title="Example ROC plot")
WVPlots::ROCPlotPair2('train',frm, "x1", "yC", TRUE,
                      'test', frm, "x2", "yC", TRUE,
                      title="Example ROC pair plot", estimate_sig = TRUE)