Predictive Target over a Shapefile
pred_target_shp.RdComputes predictions over a shapefile using outputs from the
pred_over_grid function.
This function allows for incorporating covariates, offsets, and optional
unstructured random effects into the predictive target.
Usage
pred_target_shp(
object,
shp,
shp_target = mean,
weights = NULL,
standardize_weights = FALSE,
col_names = NULL,
include_covariates = TRUE,
include_nugget = FALSE,
include_cov_offset = FALSE,
include_re = FALSE,
f_target = NULL,
pd_summary = NULL
)Arguments
- object
Output from `pred_over_grid`, a RiskMap.pred.re object.
- shp
Spatial dataset (sf or data.frame) representing the shapefile over which predictions are computed.
- shp_target
Function defining the aggregation method for shapefile targets (default is mean).
- weights
Optional numeric vector of weights for spatial predictions.
- standardize_weights
Logical indicating whether to standardize weights (default is FALSE).
- col_names
Column name or index in 'shp' containing region names.
- include_covariates
Logical indicating whether to include covariates in predictions (default is TRUE).
- include_nugget
Logical indicating whether to include the nugget effect (default is FALSE).
- include_cov_offset
Logical indicating whether to include covariate offset in predictions (default is FALSE).
- include_re
Logical indicating whether to include random effects in predictions (default is FALSE).
- f_target
List of target functions to apply to the linear predictor samples.
- pd_summary
List of summary functions (e.g., mean, sd) to summarize target samples.
Value
An object of class 'RiskMap_pred_target_shp' containing computed targets, summaries, and associated spatial data.
Details
This function computes predictive targets or summaries over a spatial shapefile using outputs from 'pred_S'. It requires the 'terra' package for spatial data manipulation and should be used with 'sf' or 'data.frame' objects representing the shapefile.