#' npfseir: Nested Particle Filter for Stochastic SEIR Epidemic Models
#'
#' Implements the online Bayesian inference framework for stochastic SEIR
#' epidemic models with latent Ornstein-Uhlenbeck transmission dynamics,
#' as described in Feng and Wang (2025).
#'
#' @section Main functions:
#' \describe{
#'   \item{\code{\link{npf_seir}}}{Run the nested particle filter.}
#'   \item{\code{\link{seir_simulate}}}{Simulate a stochastic SEIR trajectory.}
#'   \item{\code{\link{cori_rt}}}{Cori-style renewal R_t estimator (illustrative).}
#'   \item{\code{\link{ou_params}}}{Exact OU discrete-time transition parameters.}
#' }
#'
#' @section S3 methods for \code{npf_seir} objects:
#' \code{print}, \code{summary}, \code{plot}, \code{predict}.
#'
#' @references
#' Feng, W. and Wang, W. (2025). Bayesian sequential inference for a stochastic SEIR model
#' with latent transmission dynamics. \emph{Preprint}.
#'
#' Crisan, D. and Miguez, J. (2018). Nested particle filters for online
#' parameter estimation in discrete-time state-space Markov models.
#' \emph{Bernoulli}, 24(4A):3039--3086.
#'
#' @importFrom stats rnorm rpois runif rgamma pgamma qgamma quantile
#'   weighted.mean median predict
#' @importFrom graphics plot lines polygon abline legend par mtext
#' @importFrom grDevices adjustcolor
#' @docType package
#' @name npfseir-package
"_PACKAGE"
