Modeltime workflow sets forecast

Source: R/modeltime_wfs_forecast.R

forecast from a set of recipes and models trained by modeltime_wfs_fit() function.

modeltime_wfs_forecast(.wfs_results, .series, .split_prop = NULL, .h = NULL)

Arguments

.wfs_results

tibble of combination of recipes and models fitted, generated with the modeltime_wfs_fit() function.
.series

time series dataframe.
.split_prop

time series split proportion.
.h

time series horizon from the modeltime_forecast() function from 'modeltime' package.

Value

a tibble containing the forecast for each model.

Details

since it uses the modeltime_forecast() function from 'modeltime' package, either the forecast can be made on new data or on a number of periods.

Examples

library(dplyr)
library(modeltime)
library(earth)

data <- sknifedatar::data_avellaneda %>%  mutate(date=as.Date(date)) %>% 
filter(date<'2012-06-01')

recipe_date <- recipes::recipe(value ~ ., data = data) %>% 
  recipes::step_date(date, features = c('dow','doy','week','month','year')) 

mars <- parsnip::mars(mode = 'regression') %>%
  parsnip::set_engine('earth')

wfsets <- workflowsets::workflow_set(
  preproc = list(
    R_date = recipe_date),
  models  = list(M_mars = mars),
  cross   = TRUE)

wffits <- sknifedatar::modeltime_wfs_fit(.wfsets = wfsets, 
                                         .split_prop = 0.8, 
                                         .serie=data)

#> ── MODEL: R_date_M_mars 
#> ✓ Training finished OK.
#> 
#> 
#> ── 1 models fitted ♥ ───────────────────────────────────────────────────────────
#> 
#> ── 0 models deleted x ──
#> 
                            
sknifedatar::modeltime_wfs_forecast(.wfs_results=wffits, 
                                    .series = data,
                                    .split_prop = 0.8) 

#> # A tibble: 1,497 x 7
#>    .model_id .model_desc .key   .index     .value .conf_lo .conf_hi
#>    <chr>     <chr>       <fct>  <date>      <dbl>    <dbl>    <dbl>
#>  1 NA        ACTUAL      actual 2009-01-01  76167       NA       NA
#>  2 NA        ACTUAL      actual 2009-01-02 102293       NA       NA
#>  3 NA        ACTUAL      actual 2009-01-03  81249       NA       NA
#>  4 NA        ACTUAL      actual 2009-01-04  79140       NA       NA
#>  5 NA        ACTUAL      actual 2009-01-05 123039       NA       NA
#>  6 NA        ACTUAL      actual 2009-01-06 120033       NA       NA
#>  7 NA        ACTUAL      actual 2009-01-07 124016       NA       NA
#>  8 NA        ACTUAL      actual 2009-01-08 123795       NA       NA
#>  9 NA        ACTUAL      actual 2009-01-09 132735       NA       NA
#> 10 NA        ACTUAL      actual 2009-01-10  90502       NA       NA
#> # … with 1,487 more rows