Estimate the total causal effect between two specified variables

Usage

estimate_total_effect(
  X,
  lingam_result,
  from_index,
  to_index,
  method = "adaptive_lasso",
  lambda = "BIC",
  init_method = "ols"
)

Arguments

X: Original data (matrix or data.frame)
lingam_result: Return value of lingam_direct()
from_index: Cause variable (1-based index or variable name)
to_index: Effect variable (1-based index or variable name)
method: Regression method ("ols", "lasso", "adaptive_lasso", "ridge"). Default is adaptive_lasso
lambda: Lambda selection ("lambda.min", "lambda.1se", "AIC", "BIC", "oracle"). Default is BIC
init_method: Method for estimating the initial weights of adaptive LASSO regression ("ols" or "ridge")

Value

Estimated total causal effect

Examples

LiNGAM_sample_1000 <- generate_lingam_sample_6()

model <- LiNGAM_sample_1000$data |>
  lingam_direct(reg_method = "ols")

LiNGAM_sample_1000$data |>
  estimate_total_effect(model, 4, 1)
#>      x3 
#> 3.03346