| 1 | #' Persistence Forecaster |
| 2 | #' |
| 3 | #' Look for the most recent similar day in the past, and return its corresponding curve. |
| 4 | #' |
| 5 | #' There are two variations, depending whether "similar day" means "same day in the week" |
| 6 | #' or "most recent day" (regardless of day type). The corresponding argument is named |
| 7 | #' "same_day": a value of TRUE implies the former interpretation (same day in week). |
| 8 | #' If the last similar day has missing values, the next one is searched, and so on until |
| 9 | #' one full serie is found (if no one is found, NA is returned). |
| 10 | #' |
| 11 | #' @docType class |
| 12 | #' @format R6 class, inherits Forecaster |
| 13 | #' @aliases F_Persistence |
| 14 | #' |
| 15 | PersistenceForecaster = R6::R6Class("PersistenceForecaster", |
| 16 | inherit = Forecaster, |
| 17 | |
| 18 | public = list( |
| 19 | predictShape = function(data, today, memory, horizon, ...) |
| 20 | { |
| 21 | # Return centered last (similar) day curve, avoiding NAs until memory is run |
| 22 | first_day = max(1, today-memory) |
| 23 | same_day = ifelse(hasArg("same_day"), list(...)$same_day, TRUE) |
| 24 | # If 'same_day', get the last known future of similar day: -7 + 1 == -6 |
| 25 | index = today - ifelse(same_day,6,0) |
| 26 | repeat |
| 27 | { |
| 28 | { |
| 29 | last_serie = data$getCenteredSerie(index)[1:horizon] |
| 30 | index = index - ifelse(same_day,7,1) |
| 31 | }; |
| 32 | if (!any(is.na(last_serie))) |
| 33 | return (last_serie); |
| 34 | if (index < first_day) |
| 35 | return (NA) |
| 36 | } |
| 37 | } |
| 38 | ) |
| 39 | ) |