This alpha release provides tools for working with panel data using partially observed Markov processes.
In particular, this package allows one to model multiple, independent units (or individuals) for each of which one has (potentially multivariate) time series data.
The basic idea driving panelPomp is to apply to a collection of units some of the pomp package facilities for implementing POMP models, simulating them, and fitting them to time series data.
Regarding fitting, as of this release, only the iterated filtering (mif2) algorithm has currently been extended to the panelPomp panel setting.
The package is authored and maintained by Carles Breto.
See the panelPomp github site for information, source code, and downloads.
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This software has been made possible by support from the U.S. National Science Foundation (Grants #EF-0545276, #EF-0430120), by the “Inference for Mechanistic Models” Working Group supported by the National Center for Ecological Analysis and Synthesis (a Center funded by N.S.F. (Grant #DEB-0553768), the University of California, Santa Barbara, and the State of California), and by the RAPIDD program of the Science & Technology Directorate, Department of Homeland Security and the Fogarty International Center, U.S. National Institutes of Health. |