seasonaldummy {forecast} | R Documentation |
seasonaldummy
and seasonaldummyf
return matrices of dummy variables suitable for use in arima
, lm
or tslm
. The last season is omitted and used as the control.
fourier
and fourierf
return matrices containing terms from a Fourier series, up to order K
, suitable for use in arima
, lm
or tslm
.
seasonaldummy(x) seasonaldummyf(x,h) fourier(x,K) fourierf(x,K,h)
x |
Seasonal time series |
h |
Number of periods ahead to forecast |
K |
Maximum order of Fourier terms |
Numerical matrix with number of rows equal to the length(x)
and number of columns equal to frequency(x)-1
(for seasonaldummy
and seasonaldummyf
or 2*K
(for fourier
or fourierf
).
Rob J Hyndman
plot(ldeaths) # Using seasonal dummy variables month <- seasonaldummy(ldeaths) deaths.lm <- tslm(ldeaths ~ month) tsdisplay(residuals(deaths.lm)) ldeaths.fcast <- forecast(deaths.lm, data.frame(month=I(seasonaldummyf(ldeaths,36)))) plot(ldeaths.fcast) # A simpler approach to seasonal dummy variables deaths.lm <- tslm(ldeaths ~ season) ldeaths.fcast <- forecast(deaths.lm, h=36) plot(ldeaths.fcast) # Using Fourier series X <- fourier(ldeaths,3) deaths.lm <- tslm(ldeaths ~ X) ldeaths.fcast <- forecast(deaths.lm, data.frame(X=I(fourierf(ldeaths,3,36)))) plot(ldeaths.fcast)