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Convert forecasts to a future frame

Source: R/make_future.R
make_future.Rd

Convert forecasts from a fable object to a standardized forecast table.

Usage

make_future(fable, context)

Arguments

fable

A fable created with forecast().

context

A named list with the identifiers for series_id, value_id, and index_id.

Value

A tibble containing forecasts in standardized future_frame format.

Details

make_future() converts the output of forecast() into a tibble with a consistent structure for downstream evaluation, plotting, and accuracy calculation.

The returned future_frame contains one row per forecasted observation, time series, split, and model. It includes the following columns:

  • the time index column specified by context$index_id;

  • the series identifier column specified by context$series_id;

  • model: the forecasting model name;

  • split: the train-test split identifier;

  • horizon: the forecast horizon within each series, split, and model;

  • point: the point forecast, taken from the .mean column of the fable.

This format is used by functions such as make_accuracy() and make_errors().

See also

Other time series cross-validation: make_split(), make_tsibble(), slice_test(), slice_train(), split_index()

Examples

library(dplyr)
library(tsibble)
library(fable)
library(fabletools)

context <- list(
  series_id = "series",
  value_id = "value",
  index_id = "index"
)

main_frame <- M4_monthly_data |>
  filter(series %in% c("M23100", "M14395"))

split_frame <- make_split(
  main_frame = main_frame,
  context = context,
  type = "first",
  value = 120,
  n_ahead = 18,
  n_skip = 17,
  n_lag = 0,
  mode = "stretch",
  exceed = FALSE
)

train_frame <- slice_train(
  main_frame = main_frame,
  split_frame = split_frame,
  context = context
) |>
  as_tsibble(
    index = index,
    key = c(series, split)
  )

model_frame <- train_frame |>
  model(
    "SNAIVE" = SNAIVE(value ~ lag("year"))
  )

fable_frame <- model_frame |>
  forecast(h = 18)

future_frame <- make_future(
  fable = fable_frame,
  context = context
)

future_frame
#> # A tibble: 90 × 6
#>       index series model  split horizon point
#>       <mth> <chr>  <chr>  <int>   <int> <dbl>
#>  1 2011 Jul M14395 SNAIVE     1       1 2145.
#>  2 2011 Aug M14395 SNAIVE     1       2 2264.
#>  3 2011 Sep M14395 SNAIVE     1       3 3253 
#>  4 2011 Okt M14395 SNAIVE     1       4 2232.
#>  5 2011 Nov M14395 SNAIVE     1       5 1556.
#>  6 2011 Dez M14395 SNAIVE     1       6  915.
#>  7 2012 Jan M14395 SNAIVE     1       7  732.
#>  8 2012 Feb M14395 SNAIVE     1       8 1367 
#>  9 2012 Mrz M14395 SNAIVE     1       9 1478.
#> 10 2012 Apr M14395 SNAIVE     1      10 1122.
#> # ℹ 80 more rows