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) , Rebeschini and van Handel (2015) , Evensen and van Leeuwen (1996) and Ionides et al. (2021) . Pre-print statistical software article: Asfaw et al. (2021) .


Reference manual

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install.packages("spatPomp") by Kidus Asfaw, 2 months ago

Browse source code at

Authors: Kidus Asfaw [aut, cre] , Aaron A. King [aut] , Edward Ionides [aut] , Joonha Park [ctb] , Allister Ho [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports foreach, dplyr, tidyr, stringr, ggplot2, abind, rlang, magrittr

Depends on pomp, methods

Suggests testthat, doParallel, parallel

Linking to pomp

System requirements: For Windows users, Rtools (see

See at CRAN