pomp: inference for partially observed Markov processes

pomp is a powerful and widely used R package for fitting and analyzing partially observed Markov process (POMP) models, with methods including particle filtering, iterated filtering, and other simulation-based inference. It is the work of Aaron King and collaborators at the University of Michigan; Dan contributed in a minor way. Linking here because it is cool!

• CRAN: https://cran.r-project.org/web/packages/pomp/index.html

People: Dan Reuman