For my problem, I am dealing with 4 rather short time series (between 21 and 31 points). I know that an intervention was applied to each of the time series for which I know the exact date.
However, I am not sure what effect the intervention is going to have on the dependent series (or if it is going to have any effect at all), so instead of applying intervention analysis methods that expect me to specify the data of intervention a priori, my plan is to look at the data to find "anomalies" or unusual values. In other words, I want to conduct an "Intervention Detection"
So far I have been trying to use the strucchange package for break point analysis. My questions about this package are the following:
- When analyzing the the time series, does strucchange consider possible arima structure?
- I know that other predictors have a relationship on with dependent variable: is it possible to consider the effect of these (and possible lagged effects, too?)
- can strucchange not only detect level changes/pulses, but trend changes as well?
- can I test for the significance of the detected breakpoints/interventions to avoid considering spurious level shifts?
Is there any (freely) available program that can help me with my question?
Edit: another question:
- strucchange or breakpoints allows me to specify how many values there need to be in one segment. The results very much depend on the number of segments I choose. Is there a rule of thumb what number works best (especially with few data points?)