panelPomp

Inference for Panel Partially Observed Markov Processes

Authors and Contributors

Carles Bretó (carles.breto@uv.es) [aut], Edward L. Ionides [aut], Aaron A. King [aut], Jesse Wheeler (jeswheel@umich.edu) [aut, cre], and Aaron Abkemeier (aaronabk@umich.edu) [ctb].

Version

GitHub	1.5.0.1
CRAN	1.5.0.0

Package Description

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 Bretó, Ionides and King (2020) “Panel Data Analysis via Mechanistic Models” doi:10.1080/01621459.2019.1604367.

Depends

type	package	version
Depends	R	>= 4.1.0
Depends	pomp	>= 4.5.2
Imports	lifecycle	*
Imports	methods	*
Suggests	knitr	*
Suggests	rmarkdown	*
Suggests	bookdown	*

License

GPL-3