R/set_benchmarking.R

In palatej/rjd3modelling: Time Series Modelling Functions with 'JDemetra+ 3.0'

#' Set Benchmarking Specification
#'
#' @param x the specification.
#' @param enabled boolean to enable the user to perform benchmarking.
#' @param target specifies the target variable for the benchmarking procedure, which can be the raw series (\code{"Original"}); or the series adjusted for calendar effects (\code{"CalendarAdjusted"}).
#' @param rho the value of the AR(1) parameter (set between 0 and 1) in the function used for benchmarking.
#' @param lambda a parameter in the function used for benchmarking that relates to the weights in the regression equation; it is typically equal to 0, 1/2 or 1.
#' @param forecast boolean indicating if the forecasts of the seasonally adjusted series and of the target variable (\code{target}) are used in the benchmarking computation so the benchmarking constrain is applied also to the forecasting period.
#' @param bias TODO
#' @export
set_benchmarking <- function(x, enabled = NA,
                             target = c(NA, "CalendarAdjusted", "Normal"),
                             rho = NA,
                             lambda = NA,
                             forecast = NA,
                             bias = c(NA, "None")) {
  UseMethod("set_benchmarking", x)
}
#' @export
set_benchmarking.default <- function(x, enabled = NA,
                                     target = c(NA, "CalendarAdjusted", "Normal"),
                                     rho = NA,
                                     lambda = NA,
                                     forecast = NA,
                                     bias = c(NA, "None")) {
  target <- match.arg(toupper(target[1]),
                      c(NA, "CALENDARADJUSTED", "NORMAL"))
  bias <- match.arg(toupper(bias)[1],
                    c(NA, "NONE"))
  if (!is.na(enabled) && is.logical(enabled)) {
    x$enabled <- enabled
  }
  if (!is.na(target)) {
    x$target <- sprintf("TARGET_%s", target)
  }
  if (!is.na(lambda)) {
    x$lambda <- lambda
  }
  if (!is.na(rho)) {
    x$rho <- rho
  }
  if (!is.na(bias)) {
    x$bias <- sprintf("BIAS_%s", bias)
  }
  if (!is.na(forecast) && is.logical(forecast)) {
    x$forecast <- forecast
  }

  x
}