spatPomp: Inference for Spatiotemporal Partially Observed Markov Processes

Inference on panel data using spatiotemporal partially-observed Markov process (SpatPOMP) models. To do so, it relies on and extends a number of facilities that the 'pomp' package provides for inference on time series data using partially-observed Markov process (POMP) models. Implemented methods include filtering and inference methods in Park and Ionides (2020) <doi:10.1007/s11222-020-09957-3>, Rebeschini and van Handel (2015) <doi:10.1214/14-AAP1061>, Evensen and van Leeuwen (1996) <doi:10.1029/94JC00572> and Ionides et al. (2021) <arXiv:2002.05211v2>. Pre-print statistical software article: Asfaw et al. (2021) <arXiv:2101.01157>.

Depends: pomp (≥ 3.3), R (≥ 4.0.0), methods
Imports: doParallel (≥ 1.0.11), parallel, foreach, dplyr, tidyr, stringr, ggplot2, abind, rlang, magrittr
LinkingTo: pomp
Suggests: testthat
Published: 2021-04-12
Author: Kidus Asfaw [aut, cre], Aaron A. King [aut], Edward Ionides [aut], Joonha Park [ctb], Allister Ho [ctb]
Maintainer: Kidus Asfaw <kasfaw at>
Contact: kasfaw at umich dot edu
License: GPL-3
NeedsCompilation: yes
SystemRequirements: For Windows users, Rtools (see
Citation: spatPomp citation info
Materials: README NEWS
CRAN checks: spatPomp results


Reference manual: spatPomp.pdf
Package source: spatPomp_0.21.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel: not available
macOS binaries: r-release: spatPomp_0.21.0.0.tgz, r-oldrel: not available


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