projection_rf {sae.projection}R Documentation

Projection RF Function

Description

This function trains a random forest model and performs domain-level estimation **without bias correction**.

Usage

projection_rf(
  data_model,
  target_column,
  predictor_cols,
  data_proj,
  domain1,
  domain2,
  psu,
  ssu = NULL,
  strata = NULL,
  weights,
  split_ratio = 0.8,
  feature_selection = TRUE
)

Arguments

data_model

The training dataset, consisting of auxiliary variables and the target variable.

target_column

The name of the target column in the data_model.

predictor_cols

A vector of predictor column names.

data_proj

The data for projection (prediction), which needs to be projected using the trained model. It must contain the same auxiliary variables as the data_model

domain1

Domain variables for survey estimation (e.g., "province")

domain2

Domain variables for survey estimation (e.g., "regency")

psu

Primary sampling units, representing the structure of the sampling frame.

ssu

Secondary sampling units, representing the structure of the sampling frame (default is NULL).

strata

Stratification variable, ensuring that specific subgroups are represented (default is NULL).

weights

Weights used for the direct estimation from data_model and indirect estimation from data_proj.

split_ratio

Proportion of data used for training (default is 0.8, meaning 80 percent for training and 20 percent for validation).

feature_selection

Selection of predictor variables (default is TRUE)

Value

A list containing the following elements:


[Package sae.projection version 0.1.4 Index]