xx_all

Maximized Covariates Matrix for Crop Yield Forecasting

datasets

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

xx_all function

A three-dimensional array with dimensions \((n_train+n_test, M)\):<dl>
<dt>n_train+n_test</dt>
<dd>Number of time points used in the training set.</dd><dt>M</dt>
<dd>Number of selected climate covariates used for modeling (<code>cdd</code>,<code>frost_days</code>,<code>rx1day</code>, <code>tg_mean</code>, <code>txgt_25</code>).</dd>
</dl>

Format

Maximized Covariates Matrix for Crop Yield Forecasting — xx_all

A three-dimensional array with dimensions \((n_train+n_test, M)\):<dl>
<dt>n_train+n_test</dt>
<dd>Number of time points used in the training set.</dd>

<dt>M</dt>
<dd>Number of selected climate covariates used for modeling (<code>cdd</code>,<code>frost_days</code>,<code>rx1day</code>, <code>tg_mean</code>, <code>txgt_25</code>).</dd>


</dl>

xx_all: Maximized Covariates Matrix for Crop Yield Forecasting

Description

Usage

Arguments

Format