External variables for a regression with ARIMA errors

fourier_terms() gives the sine and cosine pairs of a seasonal period up to order harmonics (those beyond half the period, which would repeat the earlier ones, are left out); seasonal_dummies() one dummy per season but the first. Both have rows rows, which must cover the series and the horizon to be forecast. Combine them, or add your own columns, with cbind().

Usage

fourier_terms(period, order, rows)

seasonal_dummies(period, rows)

Arguments

period: The seasonal period (need not be a whole number for Fourier terms).
order: Harmonics.
rows: Rows: the length of the series plus the horizon.

Value

A tibble.

Examples

x <- fourier_terms(12, 3, length(AirPassengers) + 12)
fit <- fit_model(model_arima(c(1, 1, 1), constant = TRUE, regressors = x), log(AirPassengers))
predict(fit, 12)
#>           Jan      Feb      Mar      Apr      May      Jun      Jul      Aug
#> 1961 6.111487 6.158341 6.212377 6.239372 6.260181 6.351994 6.483706 6.501204
#>           Sep      Oct      Nov      Dec
#> 1961 6.353833 6.188675 6.142377 6.182586