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: 2026-04-22 15:30:05 UTC; weinanwang
Author: Weinan Wang [aut, cre]
Maintainer: Weinan Wang <ww@ou.edu>
Repository: CRAN
Date/Publication: 2026-04-24 18:40:07 UTC
Built: R 4.6.0; ; 2026-04-25 11:59:18 UTC; unix
