Gaussian and Student-t Copula Models for Count Time Series R package gctsc version 0.2.5 CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries) Provides likelihood-based inference for Gaussian and Student-t copula models for univariate count time series. Supports Poisson, negative binomial, binomial, beta-binomial, and zero-inflated marginals with ARMA dependence structures. Includes simulation, maximum-likelihood estimation, residual diagnostics, and predictive inference. Implements Time Series Minimax Exponential Tilting (TMET) <doi:10.1016/j.csda.2026.108344>, an adaptation of minimax exponential tilting of Botev (2017) <doi:10.1111/rssb.12162>. Also provides a linear-cost implementation of the Geweke–Hajivassiliou–Keane (GHK) simulator following Masarotto and Varin (2012) <doi:10.1214/12-EJS721>, and the Continuous Extension (CE) approximation of Nguyen and De Oliveira (2025) <doi:10.1080/02664763.2025.2498502>. The package follows the S3 design philosophy of 'gcmr' but is developed independently. Software Depends: R (>= 3.5) Imports: Rcpp, Matrix, TruncatedNormal, VGAM, truncnorm, nlme, car LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Quynh Nguyen <nqnhu2209@gmail.com> Comprehensive R Archive Network (CRAN) Quynh Nguyen [aut, cre] GPL-3 2026-07-12 application/tgz https://CRAN.R-project.org/package=gctsc doi:10.32614/CRAN.package.gctsc