gctsc: Modeling Count Time Series Data via Gaussian Copula Models
Gaussian copula models for count time series. Includes simulation utilities, likelihood approximation, maximum-likelihood estimation, residual diagnostics, and predictive inference. Implements the Time Series Minimax Exponential Tilting (TMET) method, an adaptation of Minimax Exponential Tilting (Botev, 2017) <doi:10.1111/rssb.12162> and the Vecchia-based tilting framework of Cao and Katzfuss (2025) <doi:10.1080/01621459.2025.2546586>. Also provides a linear-cost implementation of the Geweke–Hajivassiliou–Keane (GHK) simulator inspired by 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 structure of 'gcmr', but all code in 'gctsc' was developed independently.
| Version: | 0.1.3 |
| Depends: | R (≥ 3.5) |
| Imports: | Rcpp,Matrix,TruncatedNormal,VGAM,car,truncnorm |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | knitr,rmarkdown,VeccTMVN,gcmr,testthat (≥ 3.0.0) |
| Published: | 2025-12-17 |
| DOI: | 10.32614/CRAN.package.gctsc (may not be active yet) |
| 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 + fileLICENSE |
| URL: | https://github.com/QNNHU/gctsc |
| NeedsCompilation: | yes |
| Citation: | gctsc citation info |
| Materials: | README |
| CRAN checks: | gctsc results |
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