Diagnostics and Models for Underdispersed Count Data R package underdisp version 0.1.0 Tools for detecting and modeling underdispersion in count data (conditional variance below the conditional mean), a phenomenon overlooked by the Poisson and negative binomial defaults. Provides a screening diagnostic that benchmarks at-risk dispersion against a zero-truncated Poisson; the continuous parameter binomial (CPB) regression and its zero-truncated variant, with an interpretable observation-specific bound and high-dimensional fixed-effects support; validated bootstrap (for coefficients) and profile-likelihood (for the dispersion parameter) inference; and quantities of interest including predicted probabilities and the implied ceiling. The likelihood is implemented in C++ for speed. Software Depends: R (>= 4.0) Imports: Rcpp, stats, MASS, VGAM, graphics, methods, numDeriv LinkingTo: Rcpp Suggests: sandwich, pscl, DHARMa, testthat (>= 3.0.0), knitr, rmarkdown, broom, modelsummary, texreg Benjamin E. Bagozzi <bagozzib@udel.edu> Comprehensive R Archive Network (CRAN) Benjamin E. Bagozzi [aut, cre] GPL-3 2026-08-20 application/tgz https://CRAN.R-project.org/package=underdisp doi:10.32614/CRAN.package.underdisp