Package: dgtf
Type: Package
Title: Variational and Monte Carlo Inference for Bayesian State-Space
        Models of Count Data
Version: 0.1.0
Authors@R: c(
    person(given = "Meini", family = "Tang", role = c("aut", "cre"),
           email = "meini.tang@gmail.com",
           comment = c(ORCID = "0000-0001-5338-8772")),
    person(given = "Raquel", family = "Prado", role = "aut",
           email = "rprado@ucsc.edu",
           comment = c(ORCID = "0000-0001-6709-7191"))
    )
Description: Bayesian inference for a general class of state-space models
    for count data, providing a unified interface to variational Bayes and
    Markov chain Monte Carlo. Models are assembled from modular components
    for the observation distribution, link function, gain function, lag
    distribution, system equation, and system error, and support Poisson
    and negative binomial observations together with seasonality terms.
    The model class and the hybrid variational approximation are
    described in Tang and Prado (2026) <doi:10.1016/j.csda.2026.108368>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
SystemRequirements: C++17
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.10), stats, utils, graphics, grDevices, ggplot2
        (>= 3.3.0)
LinkingTo: Rcpp, RcppArmadillo, BH, RcppProgress, pg
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, EpiEstim
Config/testthat/edition: 3
URL: https://github.com/minimeini/dgtf
BugReports: https://github.com/minimeini/dgtf/issues
VignetteBuilder: knitr
Config/roxygen2/version: 8.1.0
Packaged: 2026-10-19 08:37:18 UTC; meinitang
Author: Meini Tang [aut, cre] (ORCID: <https://orcid.org/0000-0001-5338-8772>),
  Raquel Prado [aut] (ORCID: <https://orcid.org/0000-0001-6709-7191>)
Maintainer: Meini Tang <meini.tang@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 12:20:12 UTC
Built: R 4.5.2; x86_64-apple-darwin20; 2026-10-28 13:11:14 UTC; unix
Archs: dgtf.so.dSYM
