I need to fit a distribution to a data set I created and decided on a kernel density distribution. For this I use
fitdist(data,'Kernel','Kernel','epanechnikov');
My data set has only values greater than zero. Unfortunately, my current implementation of the kernel fit ignores that boundary condition. From literature and also this great youtube video I know that it is possible to create a kernel distribution that respects such a boundary condition by using a mirroring method.
Is there a possibility within the fitdist function or by some other method to easily implement this boundary condition?
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