ETS() Non Seasonal data error

[pstamolampros]

install.packages("forecast") library("forecast")

data(AirPassengers) AP <- AirPassengers

This will return an (M,Ad,M) model fit<- ets(AP)

same observations but will return (M,N,N) fit2<- ets(AP[1:144])

this return an error no seasonal data fit3 <- ets(AP[1:144], model="MAM")

[robjhyndman]

By subsetting the data in this way, it loses its time series attributes including the frequency, so ets() does not know it is seasonal data. The correct way to subset a time series without losing information is to use either subset(AP, end=144), or window(AP, end=c(1960,12)).

[pstamolampros]

Thank you for your reply and for sharing your great work

I do have another question about the qualified model from the automatic ets(). From the output below I understand that the MMM model is better based on the information criteria but the "ZZZ" selects the MAM. What Am I missing?

`> data(AirPassengers)

AP <- AirPassengers AP.train <- window(AP, end=c(1958,3)) AP.test <- window(AP, start=c(1958,4)) ets(AP.train , model="ZZZ") ETS(M,Ad,M)

Call: ets(y = AP.train, model = "ZZZ")

Smoothing parameters: alpha = 0.75 beta = 0.0233 gamma = 1e-04 phi = 0.98

Initial states: l = 120.3561 b = 1.7593 s = 0.9013 0.799 0.9181 1.06 1.2002 1.2147 1.1032 0.9775 0.9877 1.0297 0.8985 0.9101

sigma: 0.0371

 AIC     AICc      BIC 

1004.257 1011.692 1053.028

ets(AP.train , model="MMM") ETS(M,Md,M)

Call: ets(y = AP.train, model = "MMM")

Smoothing parameters: alpha = 0.7209 beta = 0.0134 gamma = 1e-04 phi = 0.9789

Initial states: l = 120.3501 b = 1.0134 s = 0.903 0.7993 0.919 1.0591 1.2002 1.2139 1.1036 0.9754 0.9858 1.0296 0.8998 0.9113

sigma: 0.037

 AIC     AICc      BIC 

1003.631 1011.065 1052.402 `

[robjhyndman]

The automatic search does not consider multiplicative trend models. See the allow.multiplicative.trend argument.