Wish you would not mind me asking questions here. I am a bit confused of the Arima() and auto.arima().
I have an irregular time series (unit is day) stored in a zoo object. It is irregular because no data on holidays and weekends.
The function as.ts() converted the zoo into a regular ts with NA interpolated. But the resulting ts has a frequency 1. So auto.arima() seemed to exclude all seasonal terms even though I specified D=1, max.D=30.
If I converted the zoo explicitly by ts(zoo, start=, frequency=340) (340 is due to exclusion of holidays and weekends), then auto.arima would include seasonal terms.
The question is, the ts is irregular and conversion by ts(..., freq=340) led to wrong time series. Is there any approaches that forecast can deal with the issue?
Wish you would not mind me asking questions here. I am a bit confused of the
Arima()
andauto.arima()
.I have an irregular time series (unit is day) stored in a
zoo
object. It is irregular because no data on holidays and weekends.The function
as.ts()
converted thezoo
into a regular ts withNA
interpolated. But the resulting ts has a frequency 1. Soauto.arima()
seemed to exclude all seasonal terms even though I specifiedD=1, max.D=30
.If I converted the
zoo
explicitly byts(zoo, start=, frequency=340)
(340 is due to exclusion of holidays and weekends), thenauto.arima
would include seasonal terms.The question is, the ts is irregular and conversion by
ts(..., freq=340)
led to wrong time series. Is there any approaches thatforecast
can deal with the issue?