Closed robjhyndman closed 3 years ago
Naming the STL decomposition in decomposition_model()
passes it to ...
, rather than the decomposition specification argument, dcmp
:
library(fpp3)
#> ── Attaching packages ────────────────────────────────────────────── fpp3 0.3 ──
#> ✓ tibble 3.0.4 ✓ tsibble 0.9.3.9000
#> ✓ dplyr 1.0.2 ✓ tsibbledata 0.2.0
#> ✓ tidyr 1.1.2 ✓ feasts 0.1.5.9000
#> ✓ lubridate 1.7.9.2 ✓ fable 0.2.1.9000
#> ✓ ggplot2 3.3.2
#> ── Conflicts ───────────────────────────────────────────────── fpp3_conflicts ──
#> x lubridate::date() masks base::date()
#> x dplyr::filter() masks stats::filter()
#> x tsibble::interval() masks lubridate::interval()
#> x dplyr::lag() masks stats::lag()
calls <- bank_calls %>%
mutate(t = row_number()) %>%
update_tsibble(index = t, regular = TRUE)
calls %>%
model(
stl = STL(Calls ~ season(period=169) + season(period=5*169))
) %>%
components() %>%
autoplot()
#> Loading required namespace: moment
my_dcmp_spec <- decomposition_model(
dcmp = STL(Calls ~ season(period=169) + season(period=5*169)),
ETS(season_adjust ~ season("N"))
)
calls %>%
model(my_dcmp_spec) %>%
forecast(h = 5*169) %>%
autoplot(tail(calls, 10*169)) + xlab("Week")
Created on 2020-11-18 by the reprex package (v0.3.0)
The ETS()
model is being used for the decomposition, which does not provide season_adjust
(I guess it could provide season_adjust
if we wanted it to).
Sorry. Dumb mistake
To replicate this, you will need the latest dev version of the fpp3 package.
Created on 2020-11-18 by the reprex package (v0.3.0)