run_regression_submodels: Run regression sub-models

In mbg: Model-Based Geostatistics

Run regression sub-models

Description

Wrapper to run many regression sub-models using the caret package

Usage

run_regression_submodels(
  input_data,
  id_raster,
  covariates,
  cv_settings,
  model_settings,
  family = "binomial",
  clamping = TRUE,
  use_admin_bounds = FALSE,
  admin_bounds = NULL,
  admin_bounds_id = "polygon_id",
  prediction_range = c(-Inf, Inf),
  verbose = TRUE
)

Arguments

input_data	A data.frame with at least the following columns: 'indicator': number of "hits' per site, e.g. tested positive for malaria 'samplesize': total population sampled at the site 'x': x position, often longitude 'y': y position, often latitude
id_raster	terra::SpatRaster with non-NA pixels delineating the extent of the study area
covariates	(list) Named list of all covariate effects included in the model, typically generated by load_covariates().
cv_settings	Named list of cross-validation settings, passed to caret::trainControl.
model_settings	Named list where the name of each header corresponds to a model run in caret::train, and the arguments correspond to the model-specific settings for that model type.
family	(character(1), default 'binomial') Statistical model family being evaluated. For Gaussian models, this function trains against the 'mean' field; for all other families, this function trains against the ratio of 'indicator':'samplesize'.
clamping	(logical(1), default TRUE) Should the predictions of individual ML models be limited to the range observed in the data?
use_admin_bounds	(logical(1), default FALSE) Use one-hot encoding of administrative boundaries as a candidate feature?
admin_bounds	(sf, default NULL) Administrative boundaries to use. Only considered if use_admin_bounds is TRUE.
admin_bounds_id	(character, default 'polygon_id') Field to use for administrative boundary one-hot encoding. Only considered if use_admin_bounds is TRUE.
prediction_range	(numeric(2), default c(-Inf, Inf)) Prediction limits for the outcome range. Used when the predictions are in a limited range, for example, 0 to 1 or -1 to 1.
verbose	(logical(1), default TRUE) Log progress for ML model fitting?

Value

List with two items:

• "models": A list containing summary objects for each regression model

• "predictions": Model predictions covering the entire id_raster

mbg documentation built on April 4, 2025, 2:06 a.m.