gctsc: Gaussian and Student-t Copula Models for Count Time Series
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.
| Version: |
0.2.0 |
| Depends: |
R (≥ 3.5) |
| Imports: |
Rcpp, Matrix, TruncatedNormal, VGAM, truncnorm |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
knitr, rmarkdown, VeccTMVN, gcmr, testthat (≥ 3.0.0) |
| Published: |
2026-03-13 |
| DOI: |
10.32614/CRAN.package.gctsc |
| Author: |
Quynh Nguyen [aut, cre],
Victor De Oliveira [aut] |
| Maintainer: |
Quynh Nguyen <nqnhu2209 at gmail.com> |
| BugReports: |
https://github.com/QNNHU/gctsc/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/QNNHU/gctsc |
| NeedsCompilation: |
yes |
| Materials: |
README |
| In views: |
TimeSeries |
| CRAN checks: |
gctsc results |
Documentation:
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