This function performs inference using a trained model, providing flexibility for different types of models such as Causal Forest, Ridge Regression, and Feedforward Neural Networks (FNNs).
Arguments
- model
A trained model object returned by the `fit_model` function.
- X
A matrix or data frame of covariates for which predictions are required.
- D
A vector of binary treatment indicators (1 for treated, 0 for untreated). Optional, depending on the model type.
- model_type
The model type for policy learning. Options include
"causal_forest","s_learner", and"m_learner". Default is"causal_forest".- learner_type
The learner type for the chosen model. Options include
"ridge"for Ridge Regression and"fnn"for Feedforward Neural Network. Default is"ridge".- model_params
A list of additional parameters to pass to the model, which can be any parameter defined in the model reference package. Defaults to
NULL.