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Estimate the total causal effect between two variables (ParceLiNGAM)

Source: R/lingam_parce.r
estimate_total_effect_parce.Rd

Analogous to estimate_total_effect(), but for lingam_parce() results, which may contain NA entries in the adjacency matrix.

Usage

estimate_total_effect_parce(
  X,
  parce_result,
  from_index,
  to_index,
  method = "adaptive_lasso",
  lambda = "BIC",
  init_method = "ols"
)

Arguments

X

Original data (matrix or data.frame)

parce_result

Return value of lingam_parce()

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, or NA (with a warning) if from_index is part of an unresolved block (its parents cannot be identified).

Examples

confounded <- generate_parce_sample(n = 500, seed = 1)
result <- lingam_parce(confounded$data, reg_method = "ols")

# A well-identified pair returns a numeric estimate
estimate_total_effect_parce(confounded$data, result, from_index = 1, to_index = 5)
#> [1] 0.4965035