pkg/R/computeError.R

   1 #' Compute error
   2 #'
   3 #' Obtain the errors between forecast and data
   4 #'
   5 #' @param data Dataset, object of class \code{Data} output of \code{getData}
   6 #' @param pred Forecast object, class \code{Forecast} output of \code{computeForecast}
   7 #' @param horizon Horizon where to compute the error
   8 #'   (<= horizon used in \code{computeForecast})
   9 #'
  10 #' @return A list (abs,MAPE) of lists (day,indices)
  11 #'
  12 #' @export
  13 computeError = function(data, pred, horizon=data$getStdHorizon())
  14 {
  15     L = forecast$getSize()
  16     mape_day = rep(0, horizon)
  17     abs_day = rep(0, horizon)
  18     mape_indices = rep(NA, L)
  19     abs_indices = rep(NA, L)
  20
  21     nb_no_NA_data = 0
  22     for (i in seq_len(L))
  23     {
  24         index = forecast$getIndexInData(i)
  25         serie = data$getSerie(index+1)[1:horizon]
  26         forecast = pred$getForecast(i)[1:horizon]
  27         if (!any(is.na(serie)) && !any(is.na(forecast)))
  28         {
  29             nb_no_NA_data = nb_no_NA_data + 1
  30             mape_increment = abs(serie - forecast) / serie
  31             mape_increment[is.nan(mape_increment)] = 0. # 0 / 0
  32             mape_increment[!is.finite(mape_increment)] = 1. # >0 / 0
  33             mape_day = mape_day + mape_increment
  34             abs_increment = abs(serie - forecast)
  35             abs_day = abs_day + abs_increment
  36             mape_indices[i] = mean(mape_increment)
  37             abs_indices[i] = mean(abs_increment)
  38         }
  39     }
  40
  41     list(
  42         "abs" = list(
  43             "day" = abs_day / nb_no_NA_data,
  44             "indices" = abs_indices),
  45         "MAPE" = list(
  46             "day" = mape_day / nb_no_NA_data,
  47             "indices" = mape_indices) )
  48 }