sigma^2 estimated as 198465069: log likelihood = -784.53, aic = 1573.06
Then I check for some outliers with the TSA package
ind 19.000000 30.000000 31.000000
lambda1 5.146045 -4.250828 4.136944
So, then I added 3 outliers at theobs 19, 30 and 31
ma1 sma1 IO-19 IO-30 IO-31
-0.1550 -0.4761 23262.107 -41275.194 20083.911
s.e. 0.1274 0.1283 8954.079 8778.279 9112.721
All of them are sigficant and really improve AIC.
So, when I tried to forecast.. most common procedures did not work.
predict(SAR011011out, n.ahead = 7, se.fit = TRUE) -->data' must be of a vector type, was 'NULL'
forecast(SAR011011out, h=3)--> 'data' must be of a vector type, was 'NULL'
I have read here that TSA does not have a predict function. But I just do not believe that is not possible to forecast incorporating outliers. what does the community use in this cases?