I have developed a simple Kernel Density Estimator in Java, based on a few dozen points (maybe up to one hundred or so) and a Gaussian kernel function. The implementation gives me the PDF and CDF of my probability distribution at any point.
I would now like to implement a simple sampling method for this KDE. An obvious choice would of course be to draw from the very set of points making up the KDE, but I would like to be able to retrieve points that are slightly different from the ones in the KDE.
I haven't found so far a sampling technique that I could easily implement to solve this problem (without depending on external libraries for numerical integration or complex computations). Any advices? I don't have specially strong requirements when it comes to precision or efficiency, my main concern is to have a sampling function that works and can be easily implemented. Thanks!