On Tue, Feb 13, 2018 at 01:30:42PM +0000, Angelo DI SENA wrote: > Hi > > I'm trying to "translate" a complex matlab script in C++ using armadillo. > I implemented some functions that are not present in armadillo, but I'm > currently blocked with ksdensity > In particular I need to use ksdensity with the following parameters > > [ky kx] = ksdensity(vector,pts,'function','cdf'); > > for probability density estimate. > > Is there any implementation of such function using mlpack/armadillo?
Hi Angelo, It has been a long-standing open issue to implement fast tree-based kernel density estimation: https://github.com/mlpack/mlpack/issues/150 But unfortunately there is no implementation available today. However, if you are just looking for something simple (if vector or pts is not too big), you can write a loop over all of the points in 'pts' to calculate the normal distribution value. There may be a little bit of complexity involved---I don't know if ksdensity() does auto-tuning of the bandwidth to be used, etc. (I have not used it before). One class that may help in mlpack is the GaussianDistribution class in src/mlpack/core/dists/gaussian_distribution.hpp. I hope this helps; let me know if I can clarify anything. Thanks! Ryan -- Ryan Curtin | "Oh man, I shot Marvin in the face." r...@ratml.org | - Vincent _______________________________________________ mlpack mailing list email@example.com http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack