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.
| Version: | 6.4 |
| Depends: | R (≥ 4.1.0) |
| Imports: | methods, stats, graphics,digest,mvtnorm,deSolve,coda,data.table |
| Suggests: | ggplot2,knitr,dplyr,tidyr,subplex,nloptr |
| Published: | 2025-11-25 |
| DOI: | 10.32614/CRAN.package.pomp |
| Author: | Aaron A. King [aut, cre], Edward L. Ionides [aut], Carles Bretó [aut], Stephen P. Ellner [ctb], Matthew J. Ferrari [ctb], Sebastian Funk [ctb], Steven G. Johnson [ctb], Bruce E. Kendall [ctb], Michael Lavine [ctb], Dao Nguyen [ctb], Eamon B. O'Dea [ctb], Daniel C. Reuman [ctb], Helen Wearing [ctb], Simon N. Wood [ctb] |
| Maintainer: | Aaron A. King <kingaa at umich.edu> |
| BugReports: | https://github.com/kingaa/pomp/issues/ |
| License: | GPL-3 |
| URL: | https://kingaa.github.io/pomp/ |
| NeedsCompilation: | yes |
| SystemRequirements: | For Windows users, Rtools (seehttps://cran.r-project.org/bin/windows/Rtools/). |
| Citation: | pomp citation info |
| Materials: | README,NEWS |
| In views: | DifferentialEquations,Epidemiology,TimeSeries |
| CRAN checks: | pomp results |