synthetic_cbn.R

#' A synthetic continuous Bayesian network
#'
#' @docType data
#'
#' @format A continuous Bayesian networks over four variables ("y1", "y2", "y3", "y4"), embedding the statement "y1" independent of "y3" given "y2".
#'     The Bayesian network is available both as an object of class \code{GBN} and as an object of class \code{CI}.
#'
#'
#' @aliases synthetic_cbn
#' @name synthetic_cbn
#'
#'@source	 C. Görgen & M. Leonelli (2020), Model-preserving sensitivity analysis for families of Gaussian distributions.  Journal of Machine Learning Research, 21: 1-32.
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#'
#' @rdname synthetic_cbn
"synthetic_gbn"

#' @rdname synthetic_cbn
"synthetic_ci"