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
Sebastian Funk
Show author detailsRolesContributorDao Nguyen
Show author detailsRolesContributorDaniel C. Reuman
Show author detailsRolesContributorSteven G. Johnson
Show author detailsRolesContributorSimon N. Wood
Show author detailsRolesContributorEdward L. Ionides
Carles Bretó
Stephen P. Ellner
Matthew J. Ferrari
Bruce E. Kendall
Michael Lavine
Show author detailsRolesContributorEamon B. O'Dea
Helen Wearing
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- Imports5 packages
- Suggests6 packages
- Reverse Depends2 packages
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- Reverse Suggests4 packages