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
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: gctsc_0.1.3.zip, r-release: gctsc_0.1.3.zip, r-oldrel: gctsc_0.1.3.zip
macOS binaries:	r-release (arm64): gctsc_0.1.3.tgz, r-oldrel (arm64): gctsc_0.1.3.tgz, r-release (x86_64): gctsc_0.1.3.tgz, r-oldrel (x86_64): gctsc_0.1.3.tgz

Linking:

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