pomp: Statistical Inference for Partially Observed Markov Processes

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.

Getting started

Package details

AuthorAaron 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]
MaintainerAaron A. King <kingaa@umich.edu>
LicenseGPL(>= 2)
Version0.69-5
URL http://pomp.r-forge.r-project.org
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("pomp", repos="http://R-Forge.R-project.org")

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pomp documentation built on May 2, 2019, 4:09 p.m.