Skip to main content

Kernel density estimation via diffusion in 1d and 2d

Project description

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.

Find the full documentation on Read-the-Docs.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

KDE_diffusion-1.0.4-py3-none-any.whl (7.6 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page