Conditional Copula Model for Crop Yield Forecasting
Compute Clayton Copula Parameter from Kendall's Tau
Compute Dynamic Gaussian Copula Correlation Parameter (rho)
Compute Dynamic Clayton Copula Parameter
Compute Dynamic Frank Copula Parameter
Compute Dynamic Gumbel Copula Parameter
Compute Dynamic Joe Copula Parameter
Fit a Bayesian Structural Time Series (BSTS) Model
Compute Frank Copula Parameter from Kendall's Tau
Compute Gumbel Copula Parameter from Kendall's Tau
Compute Joe Copula Parameter from Kendall's Tau
Generalized Log-Likelihood Function for 2D Copula-GEV Model
Compute Log-Likelihood for a Generalized Dynamic Copula-GEV Model
Compute Log-Likelihood for a Generalized Dynamic Copula Model without ...
Compare Forecasts from Two Models
Plot Observed Data and BSTS Forecast
A Special Case of simulation_generalized in 2 Dimensions
Simulate Multivariate Crop Yield Data Using a Generalized Copula-BSTS ...
Simulate Multivariate Crop Yield Data Using a Generalized Copula-GEV-B...
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>.