Get test data for prediction based on longest lag period

Based on the longest lag period in the recipe, get_test_data() creates an epi_df with columns geo_value, time_value and other variables in the original dataset, which will be used to create features necessary to produce forecasts.

Usage

get_test_data(recipe, x)

Arguments

recipe

A recipe object.

x

An epi_df. The typical usage is to pass the same data as that used for fitting the recipe.

Value

An object of the same type as x with columns geo_value, time_value, any additional keys, as well other variables in the original dataset.

Details

The minimum required (recent) data to produce a forecast is equal to the maximum lag requested (on any predictor) plus the longest horizon used if growth rate calculations are requested by the recipe. This is calculated internally.

Examples

# create recipe
rec <- epi_recipe(covid_case_death_rates) %>%
  step_epi_ahead(death_rate, ahead = 7) %>%
  step_epi_lag(death_rate, lag = c(0, 7, 14)) %>%
  step_epi_lag(case_rate, lag = c(0, 7, 14))
get_test_data(recipe = rec, x = covid_case_death_rates)
#> An `epi_df` object, 840 x 4 with metadata:
#> * geo_type  = state
#> * time_type = day
#> * as_of     = 2022-05-31
#> 
#> # A tibble: 840 × 4
#>    geo_value time_value case_rate death_rate
#>  * <chr>     <date>         <dbl>      <dbl>
#>  1 ak        2021-12-17      23.1      1.19 
#>  2 al        2021-12-17      15.6      0.290
#>  3 ar        2021-12-17      23.4      0.467
#>  4 as        2021-12-17       0        0    
#>  5 az        2021-12-17      41.2      1.04 
#>  6 ca        2021-12-17      16.9      0.158
#>  7 co        2021-12-17      30.5      0.578
#>  8 ct        2021-12-17      64.8      0.120
#>  9 dc        2021-12-17      50.4      0.140
#> 10 de        2021-12-17      67.9      0.333
#> # ℹ 830 more rows