R/internal_inherit_params.R

In CausalQueries: Make, Update, and Query Binary Causal Models

#' Create parameter documentation to inherit
#'
#' @param model A \code{causal_model}. A model object generated by
#'   \code{\link{make_model}}.
#' @param query A character string. An expression defining nodal types to
#'   interrogate \code{\link{realise_outcomes}}. An expression of the form
#'   "Y[X=1]" asks for the value of Y when X is set to 1
#' @param join_by A logical operator. Used to connect causal statements:
#'   \emph{AND} ('&') or \emph{OR} ('|'). Defaults to '|'.
#' @param parameters A vector of real numbers in [0,1]. Values of parameters to
#'   specify (optional). By default, parameters is drawn from
#'   \code{model$parameters_df}.
#' @param P A \code{data.frame}. Parameter matrix. Not required but may be
#'   provided to avoid repeated computation for simulations.
#' @param A A \code{data.frame}. Ambiguity matrix. Not required but may be
#'   provided to avoid repeated computation for simulations.
#' @param data A \code{data.frame}.  Data of nodes that can take three values:
#'   0, 1, and NA. In long form as generated by \code{\link{make_events}}
#' @param data_events A \code{data.frame}. It must be compatible with nodes in
#'   \code{model}. The default columns are
#'   \code{event}, \code{strategy} and \code{count}.
#' @param node A character string. The quoted name of a node.
#' @param statement A character string. A quoted causal statement.
#' @param using A character string. Indicates whether to
#'   use `priors`, `posteriors` or `parameters`.
#' @param n_draws An integer. If no prior distribution is provided,
#'   generate prior distribution with \code{n_draws} number of draws.
#'
#' @return This function does not return anything. It is used to
#'   inherit roxygen documentation
#' @keywords internal
#'
CausalQueries_internal_inherit_params <- function(model,
                                                  query,
                                                  join_by,
                                                  parameters,
                                                  P,
                                                  A,
                                                  data,
                                                  data_events,
                                                  node,
                                                  statement,
                                                  using,
                                                  n_draws){

}