| 1 | #' Average Forecaster |
| 2 | #' |
| 3 | #' Pointwise average of all the series of the same day of week in the past. |
| 4 | #' |
| 5 | #' For example, if the current day (argument "today") is a tuesday, then all series |
| 6 | #' corresponding to wednesdays in the past (until the beginning or memory limit) are |
| 7 | #' averaged to provide a smooth prediction. This forecast will most of the time be wrong, |
| 8 | #' but will also look plausible enough. |
| 9 | #' |
| 10 | #' @usage # AverageForecaster$new(pjump) |
| 11 | #' |
| 12 | #' @docType class |
| 13 | #' @format R6 class, inherits Forecaster |
| 14 | #' @aliases F_Average |
| 15 | #' |
| 16 | AverageForecaster = R6::R6Class("AverageForecaster", |
| 17 | inherit = Forecaster, |
| 18 | |
| 19 | public = list( |
| 20 | predictShape = function(data, today, memory, predict_from, horizon, ...) |
| 21 | { |
| 22 | avg = rep(0., (horizon-predict_from+1)) |
| 23 | first_day = max(1, today-memory) |
| 24 | index <- today |
| 25 | nb_no_na_series = 0 |
| 26 | repeat |
| 27 | { |
| 28 | index = index - 7 |
| 29 | if (index < first_day) |
| 30 | break |
| 31 | serie_on_horizon = data$getCenteredSerie(index)[predict_from:horizon] |
| 32 | if (!any(is.na(serie_on_horizon))) |
| 33 | { |
| 34 | avg = avg + serie_on_horizon |
| 35 | nb_no_na_series = nb_no_na_series + 1 |
| 36 | } |
| 37 | } |
| 38 | avg / nb_no_na_series |
| 39 | } |
| 40 | ) |
| 41 | ) |