Bayesian Zero-Inflated Negative Binomial Gaussian Process Models R package ZINB.GP version 1.0.0 Fits Bayesian zero-inflated negative binomial regression models with Gaussian process random effects for spatial, temporal, or spatiotemporal count data. Provides Markov chain Monte Carlo sampling, configurable random effects in the zero-inflation and count components, and posterior predictive draws. Implements a full GP version of the methods described by He and Huang (2024) <doi:10.1016/j.jspi.2023.106098>. Software Imports: BayesLogit, LaplacesDemon, MASS, Matrix, msm, mvtnorm, stats Suggests: coda, knitr, posterior, rmarkdown, testthat (>= 3.0.0) Hsin-Hsiung Huang <hsin.huang@ucf.edu> Comprehensive R Archive Network (CRAN) Mahlon Scott [aut], Qing He [aut], Hsin-Hsiung Huang [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-7150-7229>) MIT + file LICENSE (https://CRAN.R-project.org/package=ZINB.GP/LICENSE) 2026-09-14 application/tgz https://CRAN.R-project.org/package=ZINB.GP doi:10.32614/CRAN.package.ZINB.GP