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gctsc

gctsc

gctsc provides fast and scalable likelihood inference for Gaussian copula models for count time series, supporting a wide range of marginals:

• Poisson
  
• Negative Binomial
  
• Binomial
  
• Beta Binomial
• Zero-Inflated Poisson (ZIP)
  
• Zero-Inflated Binomial (ZIB)
  
• Zero-Inflated Beta-Binomial (ZIBB)

The package implements several likelihood approximation methods — including the proposed
TMET (Time Series Minimax Exponential Tilting) and GHK — and exploits the ARMA dependence structure for efficient high-dimensional computation.

Additional features include simulation utilities, residual diagnostic tools, and one-step prediction.

Reference

If you use this package in published work, please cite:

Nguyen, N. & De Oliveira, V. (2025).
Likelihood Inference in Gaussian Copula Models for Count Time Series via Minimax Exponential Tilting.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.