Pseudo-Observations of BSTS Residuals 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

uu function

A matrix with dimensions \((n_train, D)\):<dl>
<dt>n_train</dt>
<dd>Number of time points used in the training set.</dd><dt>D</dt>
<dd>Number of regions analyzed (<code>Dufferin</code>, <code>Wellington</code>).</dd>
</dl>

Format

Pseudo-Observations of BSTS Residuals for Crop Yield Forecasting — uu

A matrix with dimensions \((n_train, D)\):<dl>
<dt>n_train</dt>
<dd>Number of time points used in the training set.</dd>

<dt>D</dt>
<dd>Number of regions analyzed (<code>Dufferin</code>, <code>Wellington</code>).</dd>


</dl>

uu: Pseudo-Observations of BSTS Residuals for Crop Yield Forecasting

Description

Usage

Arguments

Format