I am trying to identify outliers from a simple time series (
ts1; see below) and subsequently fit an ARIMA model on the adjusted ts (w/o the outliers). Appologies, if the questions below are beginner's questions.
I have a question concerning the fitted values for the tsoutliers package in R.
I thought that the package identifies outliers iteratively, thereby fitting an ARIMA model. I am not not sure now, how to interpret the output of ?tso
What I do:
tt_out <- tso(ts, types=c("AO")) plot(tt_out)
So from these two plots, I can tell that one outlier was correctly identified (at t=172), however, the fitted values still incorporate the outlier. So what are they for?
If I want to run ARIMA without the outliers do I need to do this:
Replace the outlier by the adjusted value (yhat) and then run ARIMA from the package
forecast. However, I thought the goal was to automatically identify and to fit the model directly.
Why is the output of
tso fit including the outliers? Do I need to use
tso to identify the outliers, and then run ARIMA seperately?