R/building.R

In bnRep: A Repository of Bayesian Networks from the Academic Literature

#' building Bayesian Network
#'
#' Sensitivity analysis in Gaussian Bayesian networks using a symbolic-numerical technique.
#'
#' @usage NULL
#'
#' @format
#' A Gaussian Bayesian network to assess the damage of reinforced concrete structures of buildings. Probabilities were given within the referenced paper. The vertices are:
#' \describe{
#'   \item{X1}{Damage assessment;}
#'   \item{X2}{Cracking state;}
#'   \item{X3}{Cracking state in shear domain;}
#'   \item{X4}{Steel corrosion;}
#'   \item{X5}{Cracking state in flexure domain;}
#'   \item{X6}{Shrinkage cracking;}
#'   \item{X7}{Worst cracking in flexure domain;}
#'   \item{X8}{Corrosion state;}
#'   \item{X9}{Weakness of the beam;}
#'   \item{X10}{Deflection of the beam;}
#'   \item{X11}{Position of the worst shear crack;}
#'   \item{X12}{Breadth of the worst shear crack;}
#'   \item{X13}{Position of the worst flexure crack;}
#'   \item{X14}{Breadth of the worst flexure crack;}
#'   \item{X15}{Length of the worst flexure cracks;}
#'   \item{X16}{Cover;}
#'   \item{X17}{Structure age;}
#'   \item{X18}{Humidity;}
#'   \item{X19}{pH value in the air;}
#'   \item{X20}{Content of chlorine in the air;}
#'   \item{X21}{Number of shear cracks;}
#'   \item{X22}{Number of flexure cracks;}
#'   \item{X23}{Shrinkage;}
#'   \item{X24}{Corrosion;}
#'    }
#'
#' @return An object of class \code{bn.fit}. Refer to the documentation of \code{bnlearn} for details.
#' @keywords GBN
#' @importClassesFrom bnlearn bn.fit
#' @references Castillo, E., & Kjærulff, U. (2003). Sensitivity analysis in Gaussian Bayesian networks using a symbolic-numerical technique. Reliability Engineering & System Safety, 79(2), 139-148.
"building"