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#' @title A model variable whose uncertainty follows a Normal distribution
#' @description An R6 class representing a model variable with Normal
#' uncertainty.
#' @details A model variable for which the uncertainty in its point estimate can
#' be modelled with a Normal distribution. The hyperparameters of the
#' distribution are the mean (\code{mu}) and the standard deviation (\code{sd})
#' of the uncertainty distribution. The value of \code{mu} is the expected value
#' of the variable. Inherits from class \code{ModVar}.
#' @docType class
#' @author Andrew J. Sims \email{andrew.sims@@newcastle.ac.uk}
#' @export
NormModVar <- R6::R6Class(
classname = "NormModVar",
lock_class = TRUE,
inherit = ModVar,
private = list(
),
public = list(
#' @description Create a model variable with normal uncertainty.
#' @param description A character string describing the variable.
#' @param units Units of the quantity; character string.
#' @param mu Hyperparameter with mean of the Normal distribution for
#' the uncertainty of the variable.
#' @param sigma Hyperparameter equal to the standard deviation of the
#' normal distribution for the uncertainty of the variable.
#' @return A \code{NormModVar} object.
initialize = function(description, units, mu, sigma) {
# create a normal distribution and check arguments
D <- NormalDistribution$new(mu, sigma)
# initialize the base class
super$initialize(description, units, D = D, k = 1L)
# return
return(invisible(self))
},
#' @description Tests whether the model variable is probabilistic.
#' @return \code{TRUE} if probabilistic.
is_probabilistic = function() {
return(TRUE)
}
)
)
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