Package: STCCGEV 1.0.0
Yongkun Li
STCCGEV: Conditional Copula Model for Crop Yield Forecasting
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>.
Authors:
STCCGEV_1.0.0.tar.gz
STCCGEV_1.0.0.tar.gz(r-4.7-any)STCCGEV_1.0.0.tar.gz(r-4.6-any)
STCCGEV_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
STCCGEV/json (API)
| # Install 'STCCGEV' in R: |
| install.packages('STCCGEV', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- copula_list - Supported copula types
- cropyields_covariates - Data of the article "Probabilistic Crop Yields Forecasts With Spatio-Temporal Conditional Copula Using Extreme Weather Covariates"
- init_params_full - Initial Parameters for 2D Pseudo-Loglikelihood Estimation
- init_params_full_G - Initial Parameters for 2D Pseudo-Loglikelihood-Generalized Estimation
- init_params_noGEV - Initial Parameters for 2D Pseudo-Loglikelihood Estimation without GEV models for covariates
- medoid_names - List containing Dufferin and Wellington
- n_test - 19
- n_train - 54
- time_all - 1950-2022
- time_test - 2004-2022
- time_train - 1950-2003
- uu - Pseudo-Observations of BSTS Residuals for Crop Yield Forecasting
- xx_all - Maximized Covariates Matrix for Crop Yield Forecasting
- xx_test - Maximized Covariates Matrix for Crop Yield Forecasting
- xx_train - Maximized Covariates Matrix for Crop Yield Forecasting
- yy_all - Crop Yield Data
- yy_test - Crop Yield Data for Testing in BSTS Models
- yy_train - Crop Yield Data for Training in BSTS Models
- zz_all - Standardized Covariates Array for Crop Yield Forecasting
- zz_test - Standardized Covariates Array for Crop Yield Forecasting
- zz_train - Standardized Covariates Array for Crop Yield Forecasting
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:67bf87bc84. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 187 | ||
| source / vignettes | OK | 226 | ||
| linux-release-x86_64 | OK | 185 | ||
| wasm-release | OK | 120 |
Exports:clayton.thetadynamic.rhodynamic.theta.claytondynamic.theta.frankdynamic.theta.gumbeldynamic.theta.joefit_bstsfrank.thetaGH.thetajoe.thetalog_likelihood_Generalizedlog_likelihood_generalized_2dlog_likelihood_noGEVplot_forecastplot_forecast_comparesimul_fun_generalized_2dsimul.fun.noGEVsimulation_generalized
Dependencies:ADGofTestBoomBoomSpikeSlabbstscliclustercolorspacecopulacpp11evdfarverggplot2gluegslgtableisobandlabelinglatticelifecycleMASSMatrixmvtnormnumDerivpcaPPpsplineR6RColorBrewerrlangrootSolveS7scalesstabledistvctrsviridisLitewithrxtszoo
