Fit a random forest using an EM algorithm

Source: R/exp_max_algorithm.R

The function fits a random forest model to FOI data point estimates at 1/6 degree resolution using an Expectation Maximization algorithm

exp_max_algorithm(parms, adm_dataset, pxl_dataset, covariates_names,
  RF_obj_path = NULL, RF_obj_name = NULL, train_dts_path = NULL,
  train_dts_name = NULL, adm_covariates = NULL)

Arguments

parms

list of user-defined parameters.
adm_dataset

dataframe of the bootstrapped dataset of foi estimates and covariates at admin unit 1 resolution (pre-processed).
pxl_dataset

dataframe of the bootstrapped dataset of foi estimates and covariates at 1/6 degree resolution.
covariates_names

character vector of covariates names.
RF_obj_path

character string of the directory for saving the random forest object model. Default = NULL.
RF_obj_name

character of name of the random forest model object to save. Default = NULL.
train_dts_path

character string of the directory for saving the training dataset. Default = NULL.
train_dts_name

character of name of the training dataset dataframe to save. Default = NULL.
adm_covariates

dataframe of global covariates at admin unit 1 resolution. Default = NULL.

Value

the random forest model object returned by ranger.