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Ferdi
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Stephan Kolassa
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I'm trying the classic AirPassengers dataset in R and tried removing the seasonal component using deSeas <- forecast::seasadj(decompose(d,"multiplicative"));, but it doesn't seem to go away.
Original data:
enter image description here
Seasonality viewed with plot(decompose(d,"multiplicative")):
enter image description here
Seasonality adjusted with

deSeas <- forecast::seasadj(decompose(d,"multiplicative"))
plot(deSeas)

enter image description here

But decompose still shows a seasonal pattern, deSeas <- seasadjplot(decompose(ddeSeas,"multiplicative"));
enter image description here
But decompose still shows a seasonal pattern:
  

enter image description here

I don't understand why there still is a seasonality. Should I de-seasonalize it again? Will arima be able to re-incorporate the single de-seasonalized or double de-seasonalized data back into the predictions that it tries to make?

I'm trying the classic AirPassengers dataset in R and tried removing the seasonal component using deSeas <- seasadj(decompose(d,"multiplicative"));, but it doesn't seem to go away.
Original data:
enter image description here
Seasonality viewed with plot(decompose(d,"multiplicative")):
enter image description here
Seasonality adjusted with deSeas <- seasadj(decompose(d,"multiplicative"));
enter image description here
But decompose still shows a seasonal pattern:
 enter image description here

I don't understand why there still is a seasonality. Should I de-seasonalize it again? Will arima be able to re-incorporate the single de-seasonalized or double de-seasonalized data back into the predictions that it tries to make?

I'm trying the classic AirPassengers dataset in R and tried removing the seasonal component using deSeas <- forecast::seasadj(decompose(d,"multiplicative")), but it doesn't seem to go away.
Original data:
enter image description here
Seasonality viewed with plot(decompose(d,"multiplicative")):
enter image description here
Seasonality adjusted with

deSeas <- forecast::seasadj(decompose(d,"multiplicative"))
plot(deSeas)

enter image description here

But decompose still shows a seasonal pattern, plot(decompose(deSeas,"multiplicative")): 

enter image description here

I don't understand why there still is a seasonality. Should I de-seasonalize it again? Will arima be able to re-incorporate the single de-seasonalized or double de-seasonalized data back into the predictions that it tries to make?

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Even after seasonality adjustment, seasonality still remains. Why?

I'm trying the classic AirPassengers dataset in R and tried removing the seasonal component using deSeas <- seasadj(decompose(d,"multiplicative"));, but it doesn't seem to go away.
Original data:
enter image description here
Seasonality viewed with plot(decompose(d,"multiplicative")):
enter image description here
Seasonality adjusted with deSeas <- seasadj(decompose(d,"multiplicative"));
enter image description here
But decompose still shows a seasonal pattern:
enter image description here

I don't understand why there still is a seasonality. Should I de-seasonalize it again? Will arima be able to re-incorporate the single de-seasonalized or double de-seasonalized data back into the predictions that it tries to make?