R: Spatio-Temporal Crop Yield Prediction

# Spatio-Temporal Crop Yield Prediction

## Documentation for package ‘STCYP’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

clayton.theta | Compute Clayton Copula Parameter from Kendall's Tau
copula_list | Supported copula types
data | Real crop yield and meteorological data of 24 regions for Ontario, Canada from 1950 to 2022 and anticipated data from 2023 to 2100.
dt | Selected data from year 1950 to 2022 and covariates including txgt27, tr18, cddcold, txgt29, and tnmean for case study.
dynamic.rho | Compute Dynamic Gaussian Copula Correlation Parameter (rho)
dynamic.theta.clayton | Compute Dynamic Clayton Copula Parameter
dynamic.theta.frank | Compute Dynamic Frank Copula Parameter
dynamic.theta.gumbel | Compute Dynamic Gumbel Copula Parameter
dynamic.theta.joe | Compute Dynamic Joe Copula Parameter
fit_bsts | Fit a Bayesian Structural Time Series (BSTS) Model
frank.theta | Compute Frank Copula Parameter from Kendall's Tau
GH.theta | Compute Gumbel Copula Parameter from Kendall's Tau
init_params_full | Initial Parameters for 3D Pseudo-Loglikelihood Estimation
joe.theta | Compute Joe Copula Parameter from Kendall's Tau
log_likelihood_noGEV_3d | Log-Likelihood Function for 3D Copula Model
medoid_names | list containing Chatham-Kent, Lambton, and Wellington
n_test | 19
n_train | 54
plot_forecast | Plot Observed Data and BSTS Forecast
plot_forecast_compare | Compare Forecasts from Two Models
simul_fun_noGEV_3d | Function to optimize the full pseudo-loglikelihood and perform new forecasts
time | 1950-2022
time_test | 2004-2022
time_train | 1950-2003
u | Pseudo-Observations of BSTS Residuals for Crop Yield Forecasting
y_test | Crop Yield Data for Testing in BSTS Models
y_train | Crop Yield Training Matrix
z_test | Standardized Covariates (Test)
z_train | Standardized Covariates (Training)