Predict Gamma Distribution Parameters for Spatial Grid
generate_gamma_predictions.RdThis function predicts the scale and shape parameters of a Gamma distribution across a spatial grid using a bivariate spatial model. It can either generate new predictions or load cached results if available.
Usage
generate_gamma_predictions(
country_code,
age_param_data,
model_params,
predictor_data,
shapefile,
cell_size = 5000,
n_sim = 5000,
ignore_cache = FALSE,
save_file = FALSE,
output_dir = here::here("03_outputs", "3a_model_outputs")
)Arguments
- country_code
A string representing the country code (e.g., "KEN").
- age_param_data
A data frame containing:
web_x, web_y: Spatial coordinates
urban: Urban/rural indicator
log_scale: Log of scale parameter at observed locations
log_shape: Log of shape parameter at observed locations
- model_params
A list containing model parameters:
par: Named vector with gamma, log_sigma2, log_phi, log_tau1
Additional parameters for extracting beta coefficients
- predictor_data
A data object containing the predictors data.
- shapefile
An sf object defining the boundary for predictions
- cell_size
Numeric. Grid cell size in meters (default: 5000)
- n_sim
Integer. Number of simulations for prediction (default: 5000)
- ignore_cache
A boolean input which is set to determine whether to ignore the existing cache and write over it. Default is set to FALSE.
- save_file
A boolean to determine whether to save prediction or not. Default is FALSE as this will require lots of space.
- output_dir
A string specifying the directory where the predictions file should be saved (default is "03_outputs/3a_model_outputs").