countSTAR: Flexible Modeling of Count Data

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 (2022) <doi:10.48550/arXiv.2110.14790>, and Kowal and Wu (2023) <doi:10.48550/arXiv.2110.12316>.

Version: 1.0.2
Depends: R (≥ 2.10)
Imports: stats, utils, coda, dbarts, FastGP, gbm, graphics, Matrix, spikeSlabGAM, splines2, randomForest, Rcpp, TruncatedNormal, truncdist, KFAS
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, bayesplot, mgcv
Published: 2023-06-30
DOI: 10.32614/CRAN.package.countSTAR
Author: Brian King [aut, cre], Dan Kowal [aut]
Maintainer: Brian King <brianking387 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: countSTAR results


Reference manual: countSTAR.pdf
Vignettes: Getting Started with countSTAR


Package source: countSTAR_1.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): countSTAR_1.0.2.tgz, r-oldrel (arm64): countSTAR_1.0.2.tgz, r-release (x86_64): countSTAR_1.0.2.tgz, r-oldrel (x86_64): countSTAR_1.0.2.tgz
Old sources: countSTAR archive


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