R/grasp-fci.R

In causalDisco: Tools for Causal Discovery on Observational Data

#' @title GRaSP-FCI Algorithm for Causal Discovery
#'
#' @description
#' Run the Greedy Relaxations of the Sparsest Permutation Fast Causal
#' Inference algorithm for causal discovery using one of several engines.
#'
#' @param engine Character; which engine to use. Must be one of:
#'   \describe{
#'     \item{\code{"tetrad"}}{\pkg{Tetrad} Java library.}
#'   }
#' @param score Character; name of the scoring function to use.
#' @param test Character; name of the conditional‐independence test.
#' @param alpha Numeric; significance level for the CI tests.
#' @param ... Additional arguments passed to the chosen engine (e.g. score and
#' algorithm parameters).
#'
#' @details
#' For specific details on the supported scores, and parameters for each engine, see:
#' \itemize{
#'  \item [TetradSearch] for \pkg{Tetrad}.
#' }
#'
#' @example inst/roxygen-examples/grasp_fci-example.R
#'
#' @inheritSection disco_note Recommendation
#' @inheritSection disco_algs_return_doc_pag Value
#' @references
#' Ramsej, J., Andrews, B., Sprites, P. (2025). Efficient Latent Variable
#' Causal Discovery: Combining Score Search and Targeted Testing.
#' <doi:10.48550/arXiv.2510.04263>.
#' @family causal discovery algorithms
#' @concept cd_algorithms
#' @export
grasp_fci <- function(
  engine = "tetrad",
  score,
  test,
  alpha = 0.05,
  ...
) {
  engine <- match.arg(engine)

  make_method(
    method_name = "grasp_fci",
    engine = engine,
    engine_fns = list(
      tetrad = function(...) {
        make_runner(engine = "tetrad", alg = "grasp_fci", ...)
      }
    ),
    score = score,
    test = test,
    alpha = alpha,
    graph_class = "PAG",
    ...
  )
}