Tools for working with partially observed Markov processes (POMPs, AKA stochastic dynamical systems, state-space models). 'pomp' 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 platform for the implementation of new inference methods.
| Version: |
1.2.1.1 |
| Depends: |
R (≥ 3.1.0), methods |
| Imports: |
stats, graphics, digest, mvtnorm, deSolve, coda, subplex, nloptr |
| Suggests: |
magrittr, plyr, reshape2, ggplot2, knitr |
| Published: |
2015-09-25 |
| Author: |
Aaron A. King [aut, cre],
Edward L. Ionides [aut],
Carles Breto [aut],
Stephen P. Ellner [ctb],
Matthew J. Ferrari [ctb],
Bruce E. Kendall [ctb],
Michael Lavine [ctb],
Dao Nguyen [ctb],
Daniel C. Reuman [ctb],
Helen Wearing [ctb],
Simon N. Wood [ctb],
Sebastian Funk [ctb] |
| Maintainer: |
Aaron A. King <kingaa at umich.edu> |
| Contact: |
kingaa at umich dot edu |
| BugReports: |
http://github.com/kingaa/pomp/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
http://kingaa.github.io/pomp |
| NeedsCompilation: |
yes |
| SystemRequirements: |
For Windows users, Rtools (see
http://cran.r-project.org/bin/windows/Rtools/). |
| Citation: |
pomp citation info |
| Materials: |
NEWS |
| In views: |
DifferentialEquations, TimeSeries |
| CRAN checks: |
pomp results |