arma.cormat

Constructs a correlation structure object for use in Gaussian copula time series models
with autoregressive moving average (ARMA) dependence.

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

arma.cormat function

<dl><dt>p</dt>
<dd>Integer. AR order (non-negative).</dd>
<dt>q</dt>
<dd>Integer. MA order (non-negative).</dd>
<dt>tau.lower</dt>
<dd>Optional vector of lower bounds for the ARMA parameters.</dd>
<dt>tau.upper</dt>
<dd>Optional vector of upper bounds for the ARMA parameters.</dd></dl>

Arguments

ARMA Correlation Structure for Copula Time Series — arma.cormat

<dl>

<dt>p</dt>
<dd>Integer. AR order (non-negative).</dd>


<dt>q</dt>
<dd>Integer. MA order (non-negative).</dd>


<dt>tau.lower</dt>
<dd>Optional vector of lower bounds for the ARMA parameters.</dd>


<dt>tau.upper</dt>
<dd>Optional vector of upper bounds for the ARMA parameters.</dd>

</dl>

arma.cormat: ARMA Correlation Structure for Copula Time Series

Description

Usage

Value

Arguments

See Also