I am trying to estimate the PDF of the radius of points distributed in a 2D plane. The points are distributed like this:
I can produce a histogram of the radius data which looks like this:
I want to use kernel density estimation to produce a better result for the radial PDF and then get the value of the derivative of the PDF at $r=0$, but I immediately run into the problem that KDE will produce non-zero probability density for negative values of the radius. Is there a simple way to use KDE for this application? Maybe with an adaptive kernel? Any help would be greatly appreciated.