print.gctsc

Displays the call, estimation method, parameter estimates, and likelihood information.

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.

Quynh Nguyen

gctsc

Modeling Count Time Series Data via Gaussian Copula Models

Victor De Oliveira

print.gctsc function

<dl><dt>x</dt>
<dd>An object of class <code>gctsc</code>.</dd>
<dt>digits</dt>
<dd>Number of significant digits to display.</dd>
<dt>...</dt>
<dd>Ignored. Included for S3 method compatibility.</dd></dl>

Arguments

Print a gctsc Model Object — print.gctsc

<dl>

<dt>x</dt>
<dd>An object of class <code>gctsc</code>.</dd>


<dt>digits</dt>
<dd>Number of significant digits to display.</dd>


<dt>...</dt>
<dd>Ignored. Included for S3 method compatibility.</dd>

</dl>

print.gctsc: Print a gctsc Model Object

Description

Usage

Value

Arguments