verification (version 1.42)

discrimination.plot: Discrimination plot

Description

This function creates a plot of discrimination plots (overlay histograms). In the context of verification, this is often used to compare the distribution of event and no-event forecasts. This may be useful in comparing any set of observations. By default, boxplots of groups appear as upper marginal plots. These may be surpressed.

Usage

discrimination.plot(group.id, value, breaks = 11, main =
"Discrimination Plot", xlim = NULL, ylim = NULL,  legend =
FALSE, leg.txt = paste("Model", sort(unique(group.id)) ),   marginal = TRUE, cols =
seq(2, length(unique(group.id)) + 1), xlab = "Forecast",  ... )

Arguments

group.id

A vector identifying groups. A histogram is created for each unique value.

value

A vector of values corresponding to the group.id vector used to create the histograms

breaks

Number of breaks in the x-axis of the histogram. The range of values is taken to be the range of prediction values.

main

Title for plot.

xlim

Range of histogram - x axis - main plot coordinates.

ylim

Range of histogram - y axis - main plot coordinates.

legend

Should there be a legend? Default = FALSE

leg.txt

Legend text. If FALSE or if a marginal plot is created, no legend is added.

cols

A vector showing the colors to be used in the histograms and in the marginal boxplots

marginal

Should a boxplots be placed in the top margin? Defaults to TRUE

xlab

Label of the x-axis on the main plot.

...

Additional plotting options.

Author

Matt Pocernich

Examples

 #  A sample forecast.  

data(disc.dat)
discrimination.plot(disc.dat$group.id, disc.dat$frcst, main = "Default  Plot")

discrimination.plot(disc.dat$group.id, disc.dat$frcst, main = "New Labels", cex = 1.2,
leg.txt = c("Low", "Med", "High" ) )

discrimination.plot(disc.dat$group.id, disc.dat$frcst, main = "Without Marginal Plots ",
marginal = FALSE)