I am trying to get the seasonal adjusted value of multiple time series using STL of feasts package.
For example, suppose I would like to get the seasonal adjusted values of turnover of the following tsibble:
tsibbledata::aus_retail
For each of state and for each of industry and for each state.
The idea is something like that:
tsibbledata::aus_retail %>%
model(
STL(. ~ trend(window = 10) + season(window = "periodic"))
) %>%
components() %>%
select(data, season_adjust)
Any suggestion on how to perform multiple seasonal adjustment using stl?
suppressPackageStartupMessages({
library(feasts)
})
seas_adj <- tsibbledata::aus_retail %>%
model(stl_model = STL(Turnover ~ trend(window = 10) +
season(window = "periodic"))) %>%
components() %>%
dplyr::select(State,Industry,Month,Turnover,season_adjust)
seas_adj
#> # A tsibble: 64,532 x 5 [1M]
#> # Key: State, Industry [152]
#> State Industry Month Turnover season_adjust
#> <chr> <chr> <mth> <dbl> <dbl>
#> 1 Australian Capita… Cafes, restaurants and ca… 1982 Apr 4.4 4.85
#> 2 Australian Capita… Cafes, restaurants and ca… 1982 May 3.4 3.21
#> 3 Australian Capita… Cafes, restaurants and ca… 1982 Jun 3.6 4.12
#> 4 Australian Capita… Cafes, restaurants and ca… 1982 Jul 4 4.06
#> 5 Australian Capita… Cafes, restaurants and ca… 1982 Aug 3.6 3.47
#> 6 Australian Capita… Cafes, restaurants and ca… 1982 Sep 4.2 3.88
#> 7 Australian Capita… Cafes, restaurants and ca… 1982 Oct 4.8 3.85
#> 8 Australian Capita… Cafes, restaurants and ca… 1982 Nov 5.4 4.68
#> 9 Australian Capita… Cafes, restaurants and ca… 1982 Dec 6.9 5.22
#> 10 Australian Capita… Cafes, restaurants and ca… 1983 Jan 3.8 6.21
#> # … with 64,522 more rows
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