panelPomp: Inference for Panel Partially Observed Markov Processes

Data analysis based on panel partially-observed Markov process (PanelPOMP) models. To implement such models, simulate them and fit them to panel data, 'panelPomp' extends some of the facilities provided for time series data by the 'pomp' package. Implemented methods include filtering (panel particle filtering) and maximum likelihood estimation (Panel Iterated Filtering) as proposed in Breto, Ionides and King (2020) "Panel Data Analysis via Mechanistic Models" <doi:10.1080/01621459.2019.1604367>.

Version: 1.1
Depends: R (≥ 4.1.0), pomp (≥ 4.5.2)
Imports: methods
Published: 2023-03-29
Author: Carles Breto ORCID iD [aut, cre], Edward L. Ionides ORCID iD [aut], Aaron A. King ORCID iD [aut]
Maintainer: Carles Breto <carles.breto at>
License: GPL-3
NeedsCompilation: no
Citation: panelPomp citation info
Materials: NEWS
CRAN checks: panelPomp results


Reference manual: panelPomp.pdf


Package source: panelPomp_1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): panelPomp_1.1.tgz, r-oldrel (arm64): panelPomp_1.1.tgz, r-release (x86_64): panelPomp_1.1.tgz, r-oldrel (x86_64): panelPomp_1.1.tgz


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