KDE-diffusion

Kernel density estimation via diffusion in 1d and 2d

Provides the fast, adaptive kernel density estimator based on linear diffusion processes for one-dimensional and two-dimensional input data as outlined in the 2010 paper by Botev et al. The reference implementation for 1d and 2d, in Matlab, was provided by the paper’s first author, Zdravko Botev. This is a re-implementation in Python, with added test coverage.