Discrimination plot
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.
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", ... )
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. |
Matt Pocernich
# 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)
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