## 13.6 Backcasting

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$Month[1] - (1:15)) %>% as_fable(index = Month, response = "Turnover", distribution = "Turnover") backcasts %>% autoplot(auscafe %>% filter(year(Month) < 1990)) + labs(title = "Backcasts of Australian food expenditure", y = "$ (billions)")

Most of the work here is in re-indexing the tsibble object and then re-indexing the fable object.