pomp
Statistical Inference for Partially Observed Markov Processes
Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.
- Version5.11
- R version≥ 4.1.0
- LicenseGPL-3
- Needs compilation?Yes
- pomp citation info
- Last release09/12/2024
Documentation
Team
Aaron A. King
Edward L. Ionides
Carles Bretó
Stephen P. Ellner
Matthew J. Ferrari
Sebastian Funk
Steven G. Johnson
Show author detailsRolesContributorBruce E. Kendall
Michael Lavine
Show author detailsRolesContributorDao Nguyen
Eamon B. O'Dea
Daniel C. Reuman
Show author detailsRolesContributorHelen Wearing
Simon N. Wood
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends1 package
- Imports7 packages
- Suggests6 packages
- Reverse Depends2 packages
- Reverse Imports2 packages
- Reverse Suggests4 packages