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 + file LICENSE
URL: https://github.com/QNNHU/gctsc
NeedsCompilation: yes
Citation: gctsc citation info
Materials: README
CRAN checks: gctsc results

Documentation:

Reference manual: gctsc.html , gctsc.pdf
Vignettes: Gaussian Copula Time Series Models for Count Data (source, R code)

Downloads:

Package source: gctsc_0.1.3.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): gctsc_0.1.3.tgz, r-oldrel (x86_64): gctsc_0.1.3.tgz

Linking:

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