rocplot: Receiver Operator Characteristic Plots

In Zelig: Everyone's Statistical Software

Description

The 'rocplot' command generates a receiver operator characteristic plot to compare the in-sample (default) or out-of-sample fit for two logit or probit regressions.

Usage

rocplot(z1, z2,
cutoff = seq(from=0, to=1, length=100), lty1="solid",
lty2="dashed", lwd1=par("lwd"), lwd2=par("lwd"),
col1=par("col"), col2=par("col"),
main="ROC Curve",
xlab = "Proportion of 1's Correctly Predicted",
ylab="Proportion of 0's Correctly Predicted",
plot = TRUE,
...
)

Arguments

z1	first model
z2	second model
cutoff	A vector of cut-off values between 0 and 1, at which to evaluate the proportion of 0s and 1s correctly predicted by the first and second model. By default, this is 100 increments between 0 and 1 inclusive
lty1	the line type of the first model (defaults to 'line')
lty2	the line type of the second model (defaults to 'dashed')
lwd1	the line width of the first model (defaults to 1)
lwd2	the line width of the second model (defaults to 1)
col1	the color of the first model (defaults to 'black')
col2	the color of the second model (defaults to 'black')
main	a title for the plot (defaults to "ROC Curve")
xlab	a label for the X-axis
ylab	a lavel for the Y-axis
plot	whether to generate a plot to the selected device
...	additional parameters to be passed to the plot

Value

if plot is TRUE, rocplot simply generates a plot. Otherwise, a list with the following is produced:

roc1	a matrix containing a vector of x-coordinates and y-coordinates corresponding to the number of ones and zeros correctly predicted for the first model.
roc2	a matrix containing a vector of x-coordinates and y-coordinates corresponding to the number of ones and zeros correctly predicted for the second model.
area1	the area under the first ROC curve, calculated using Reimann sums.
area2	the area under the second ROC curve, calculated using Reimann sums.

Zelig documentation built on Jan. 8, 2021, 2:26 a.m.