Skip to main content

Bootstrap particle filter for epidemic forecasting

Project description

Latest version Journal of Open Source Software Documentation Test cases Test coverage

Description

A bootstrap particle filter that can be used for recursive Bayesian estimation and forecasting. See the online documentation for tutorials, how-to guides, and API documentation.

License

The code is distributed under the terms of the BSD 3-Clause license (see LICENSE), and the documentation is distributed under the terms of the Creative Commons BY-SA 4.0 license.

Installation

To install the latest release:

pip install pypfilt

To install the latest release with plotting support (requires matplotlib):

pip install pypfilt[plot]

To install the latest development version, clone this repository and run:

pip install .

Citation

If you use pypfilt, please cite our JOSS article and an archived release of the software (see CITATION.cff).

@article{pypfilt,
  author = {Moss, Robert},
  title = {pypfilt: a particle filter for {Python}},
  journal = {Journal of Open Source Software},
  volume = {9},
  issue = {96},
  pages = {6276},
  year = {2024},
  doi = {10.21105/joss.06276},
  note = {Please cite this article and an archived release (see CITATION.cff)},
}

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

pypfilt-0.8.3-py3-none-any.whl (106.2 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