npfseir: Nested Particle Filter for Stochastic SEIR Epidemic Models

Implements the online Bayesian inference framework for joint state and parameter estimation in a stochastic Susceptible-Exposed-Infectious-Recovered (SEIR) epidemic model with a time-varying transmission rate. The log-transmission rate is modelled as a latent Ornstein-Uhlenbeck (OU) process with exact Gaussian discrete-time transitions. Inference is performed via the nested particle filter (NPF) of Crisan and Miguez (2018) <doi:10.3150/17-BEJ954>, which maintains an outer particle layer over the OU hyperparameters and, for each outer particle, an inner bootstrap filter over epidemic states. The Cori-style renewal-equation estimator follows Cori et al. (2013) <doi:10.1093/aje/kwt133>. The package also provides utilities for simulation, posterior summarisation, and forecasting.

Version:	0.2.1
Imports:	stats, graphics, grDevices
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-04-24
DOI:	10.32614/CRAN.package.npfseir
Author:	Weinan Wang [aut, cre]
Maintainer:	Weinan Wang <ww at ou.edu>
License:	MIT + file LICENSE
NeedsCompilation:	no
Materials:	README
CRAN checks:	npfseir results

Documentation:

Reference manual:	npfseir.html , npfseir.pdf
Vignettes:	Getting started with npfseir (source, R code)

Downloads:

Package source:	npfseir_0.2.1.tar.gz
Windows binaries:	r-devel: npfseir_0.2.1.zip, r-release: npfseir_0.2.1.zip, r-oldrel: npfseir_0.2.1.zip
macOS binaries:	r-release (arm64): npfseir_0.2.1.tgz, r-oldrel (arm64): npfseir_0.2.1.tgz, r-release (x86_64): npfseir_0.2.1.tgz, r-oldrel (x86_64): npfseir_0.2.1.tgz

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