GH.theta

Computes the Gumbel-Hougaard copula dependence parameter based on Kendall's tau.

Provides functions to model and forecast crop yields using a spatial temporal conditional copula approach.
The package incorporates extreme weather covariates and Bayesian Structural Time Series models to analyze crop
yield dependencies across multiple regions. Includes tools for fitting, simulating, and visualizing results.
This method build upon established R packages, including 'Hofert' 'et' 'al'. (2025) <doi:10.32614/CRAN.package.copula>,
'Scott' (2024) <doi:10.32614/CRAN.package.bsts>, and 'Stephenson' 'et' 'al'. (2024) <doi:10.32614/CRAN.package.evd>.

Yongkun Li

STCCGEV

Conditional Copula Model for Crop Yield Forecasting

Marie Michaelides

Mélina Mailhot

GH.theta function

<dl><dt>tau</dt>
<dd>Numeric, Kendall's tau correlation coefficient.</dd></dl>

Arguments

Compute Gumbel Copula Parameter from Kendall's Tau — GH.theta

<dl>

<dt>tau</dt>
<dd>Numeric, Kendall's tau correlation coefficient.</dd>

</dl>

GH.theta: Compute Gumbel Copula Parameter from Kendall's Tau

Description

Usage

Value

Arguments