Plotting histogram overlayed with kernel estimator

Hi Joffre,

It is possible to overlay a histogram onto a KDE of the corresponding raw data. The easiest way to do this is to:

1. Plot the KDE using the kernelDensity function.
2. Add overlay the histogram using the plotAddHistF function.

/*
** Loadd data
*/
fname = getGAUSSHome("examples/winevolatileacidity.csv");
dataset = loadd(fname);
 
// Example One:
// Full sample normal density
struct kernelDensityResults krslt1;
krslt1 = kernelDensity(dataset[., "volatile acidity"]);
 
// Add histogram of raw data
// using frequencies with 50 bins
plotAddHistF(dataset[., "volatile acidity"], 50);

Note that this will plot the histogram on the same y-axis as the KDE. For better appearance, you can use a plotControl structure to plot the histogram on the right y-axis:

/*
** Loadd data
*/
fname = getGAUSSHome("examples/winevolatileacidity.csv");
dataset = loadd(fname);
 
// Full sample normal density
struct kernelDensityResults krslt1;
krslt1 = kernelDensity(dataset[., "volatile acidity"]);
 
// Use plot control structure to plot 
// new graph on right axis
struct plotControl ctl;
ctl = plotGetDefaults("bar");
 
// Specify to plot histogram
// on right y-axis
plotSetWhichYAxis(&ctl, "right");
 
// Add histogram of raw data
// using frequency with 100 bins
plotAddHist(ctl, dataset[., "volatile acidity"], 50);

Eric, thank you! This is very helpful, particularly the second example. That solves the messy scaling issue across the empirical distribution and the kernel function.

Joffre