This function allows you to specify the method used to reconcile forecasts in accordance with its key structure.
reconcile(.data, ...)
# S3 method for mdl_df
reconcile(.data, ...)A mable.
Reconciliation methods applied to model columns within .data.
library(fable)
lung_deaths_agg <- as_tsibble(cbind(mdeaths, fdeaths)) %>%
aggregate_key(key, value = sum(value))
lung_deaths_agg %>%
model(lm = TSLM(value ~ trend() + season())) %>%
reconcile(lm = min_trace(lm)) %>%
forecast()
#> # A fable: 72 x 5 [1M]
#> # Key: key, .model [3]
#> key .model index value .mean
#> <chr*> <chr> <mth> <dist> <dbl>
#> 1 fdeaths lm 1980 Jan N(794, 5606) 794.
#> 2 fdeaths lm 1980 Feb N(778, 5606) 778.
#> 3 fdeaths lm 1980 Mar N(737, 5606) 737.
#> 4 fdeaths lm 1980 Apr N(577, 5606) 577.
#> 5 fdeaths lm 1980 May N(456, 5606) 456.
#> 6 fdeaths lm 1980 Jun N(386, 5606) 386.
#> 7 fdeaths lm 1980 Jul N(379, 5606) 379.
#> 8 fdeaths lm 1980 Aug N(335, 5606) 335.
#> 9 fdeaths lm 1980 Sep N(340, 5606) 340.
#> 10 fdeaths lm 1980 Oct N(413, 5606) 413.
#> # ℹ 62 more rows