panelPomp package - RDocumentation

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panelPomp

an R package for inference on panel partially observed Markov processes

This package allows performing 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>.

The latest version of the package can be installed from this GitHub source using devtools::install_github('panelPomp-org/panelPomp')

Installing the current CRAN version is also possible using install.packages("panelPomp")

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Version

Install

install.packages('panelPomp')

Monthly Downloads

191

Version

1.7.0.0

License

GPL-3

Maintainer

Jesse Wheeler

Last Published

May 9th, 2025

Functions in panelPomp (1.7.0.0)

Constructing panelPomp objects

panelPomp plotting facilities

panel_logmeanexp

Log-mean-exp for panels

coef<-,pfilterd.ppomp-method

Modifying parameters of filtered objects

panelPomp-package

Inference for PanelPOMPs (Panel Partially Observed Markov Processes)

panelPomp_methods

Manipulating panelPomp objects

panelRandomWalk

Panel random walk model

Manipulating panelPomp object parameter formats

Particle filtering for panel data

Extract units of a panel model

Extract unit-specific parameters from a panelPomp object

Set shared parameters of a panelPomp object

Simulations of a panel of partially observed Markov process

Extract log likelihood of units of panel models

Set unit-specific parameters of a panelPomp object

Extract shared parameters from a panelPomp object

Interpret shortcuts for sQuote()s and dQuote()s in character objects

He et al. 2010 twenty UK cities weekly reported measles data

Weekly reported measles data for 362 locations in the UK

Internal function for modifying pparamArray in Mif2

#' Create design matrix for panelPomp calculations

Panel Gompertz model

Internal function for modifying pparamArray in Mif2

PIF: Panel iterated filtering

Coercing panelPomp objects as list, pompList or data.frame

panelGompertzLikelihood

Likelihood for a panel Gompertz model via a Kalman filter

Get single column or row without dropping names

Make a panelPomp model using UK measles data.

Handling of loglikelihood replicates