Package: countSTAR
Type: Package
Title: Flexible Modeling of Count Data
Version: 1.2.1
Authors@R: c(
    person(given="Brian", family="King", email = "brianking387@gmail.com", role = c("aut", "cre")),
    person(given="Dan", family = "Kowal", email = "daniel.r.kowal@gmail.com", role = "aut"))
Description: For Bayesian and classical inference and prediction with
        count-valued data, Simultaneous Transformation and Rounding
        (STAR) Models provide a flexible, interpretable, and
        easy-to-use approach. STAR models the observed count data using
        a rounded continuous data model and incorporates a
        transformation for greater flexibility. Implicitly, STAR
        formalizes the commonly-applied yet incoherent procedure of (i)
        transforming count-valued data and subsequently (ii) modeling
        the transformed data using Gaussian models. STAR is
        well-defined for count-valued data, which is reflected in
        predictive accuracy, and is designed to account for
        zero-inflation, bounded or censored data, and over- or
        underdispersion. Importantly, STAR is easy to combine with
        existing MCMC or point estimation methods for continuous data,
        which allows seamless adaptation of continuous data models
        (such as linear regressions, additive models, BART, random
        forests, and gradient boosting machines) for count-valued data.
        The package also includes several methods for modeling count
        time series data, namely via warped Dynamic Linear Models. For
        more details and background on these methodologies, see the
        works of Kowal and Canale (2020) <doi:10.1214/20-EJS1707>,
        Kowal and Wu (2022) <doi:10.1111/biom.13617>, King and Kowal
        (2023) <doi:10.1214/23-BA1394>, and Kowal and Wu (2023)
        <doi:10.48550/arXiv.2110.12316>.
License: GPL (>=2)
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo
Imports: stats, utils, graphics, Rcpp
Suggests: bayesplot, coda, dbarts, FastGP, gbm, KFAS, knitr, Matrix,
        mgcv, randomForest, rmarkdown, spikeSlabGAM, splines2,
        TruncatedNormal, truncdist
VignetteBuilder: knitr
URL: https://bking124.github.io/countSTAR/
        https://github.com/bking124/countSTAR
BugReports: https://github.com/bking124/countSTAR/issues
Depends: R (>= 2.10)
LazyData: true
Config/roxygen2/version: 8.1.0
Repository: https://bking124.r-universe.dev
Date/Publication: 2026-08-20 22:08:39 UTC
RemoteUrl: https://github.com/bking124/countstar
RemoteRef: HEAD
RemoteSha: 9003fd4b0931780002c1d4e775087e785136cc6b
NeedsCompilation: yes
Packaged: 2026-09-19 09:21:23 UTC; root
Author: Brian King [aut, cre],
  Dan Kowal [aut]
Maintainer: Brian King <brianking387@gmail.com>
Built: R 4.6.0; wasm32-unknown-emscripten; 2026-09-19 09:23:53 UTC; unix
