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:	1.4
Depends:	R (≥ 4.1.0), pomp (≥ 4.5.2)
Imports:	lifecycle, methods
Suggests:	knitr, rmarkdown, bookdown
Published:	2024-09-12
DOI:	10.32614/CRAN.package.panelPomp
Author:	Carles Breto [aut], Edward L. Ionides [aut], Aaron A. King [aut], Jesse Wheeler [aut, cre]
Maintainer:	Jesse Wheeler <jeswheel at umich.edu>
License:	GPL-3
NeedsCompilation:	no
Citation:	panelPomp citation info
Materials:	README NEWS
CRAN checks:	panelPomp results

Documentation:

Reference manual:	panelPomp.pdf
Vignettes:	getting-started (source, R code)

Downloads:

Package source:	panelPomp_1.4.tar.gz
Windows binaries:	r-devel: panelPomp_1.4.zip, r-release: panelPomp_1.4.zip, r-oldrel: panelPomp_1.4.zip
macOS binaries:	r-release (arm64): panelPomp_1.4.tgz, r-oldrel (arm64): panelPomp_1.4.tgz, r-release (x86_64): panelPomp_1.4.tgz, r-oldrel (x86_64): panelPomp_1.4.tgz
Old sources:	panelPomp archive

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