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