Package: npfseir
Title: Nested Particle Filter for Stochastic SEIR Epidemic Models
Version: 0.2.1
Date: 2026-04-22
Authors@R: person("Weinan", "Wang",
    email = "ww@ou.edu",
    role  = c("aut", "cre"))
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: stats, graphics, grDevices
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-10-12 11:26:36 UTC; root
Author: Weinan Wang [aut, cre]
Maintainer: Weinan Wang <ww@ou.edu>
Repository: https://wwang-math.r-universe.dev
Date/Publication: 2026-04-24 20:05:00 UTC
RemoteUrl: https://github.com/cran/npfseir
RemoteRef: HEAD
RemoteSha: 6b776c32d3bb18ba8c28e0670326dffea6914fa5