Sometimes it is useful to “backcast” a time series — that is, forecast in reverse time. Although there are no in-built R functions to do this, it is easy to implement by creating a new time index.
Suppose we want to extend our Australian takeaway to the start of 1981 (the actual data starts in April 1982).
backcasts <- auscafe |> mutate(reverse_time = rev(row_number())) |> update_tsibble(index = reverse_time) |> model(ets = ETS(Turnover ~ season(period = 12))) |> forecast(h = 15) |> mutate(Month = auscafe$Month - (1:15)) |> as_fable(index = Month, response = "Turnover", distribution = "Turnover") backcasts |> autoplot(auscafe |> filter(year(Month) < 1990)) + labs(title = "Backcasts of Australian food expenditure", y = "$ (billions)")
Most of the work here is in re-indexing the
tsibble object and then re-indexing the