Finds the optimal ridge penalty for local linear causal prediction.
tune_ll_causal_forest(
forest,
linear.correction.variables = NULL,
ll.weight.penalty = FALSE,
num.threads = NULL,
lambda.path = NULL
)
A list of lambdas tried, corresponding errors, and optimal ridge penalty lambda.
The forest used for prediction.
Variables to use for local linear prediction. If left null, all variables are used. Default is NULL.
Option to standardize ridge penalty by covariance (TRUE), or penalize all covariates equally (FALSE). Defaults to FALSE.
Number of threads used in training. If set to NULL, the software automatically selects an appropriate amount.
Optional list of lambdas to use for cross-validation.