tutorials

Introduction to the pypomp package for partially observed Markov process models

This is a basic introduction for new users.

Simulation-based Inference for Epidemiological Dynamics using pypomp

This short course is especially relevant for readers interested in pypomp for epidemiological or ecological applications. However, the methodology is sufficiently general to be relevant to all those interested in inference for partially observed Markov process models in any application area. The materials build on a previous short course that presented the material using the R pomp package.

Notes

  1. Code documentation is available on the pypomp Read the Docs page.
  2. Source code is available from the pypomp GitHub repository.
  3. pypomp is on PyPI.
  4. pypomp is in active development, and we are still experimenting with how to present material. Please get in touch if you are reading this and you have feedback! You are welcome to email pypomp-org@umich.edu, or you can communicate with the development team via GitHub.
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