I am dealing with time series and using statsmodel's ARIMA to fit a model using maximum likelihood estimation. When I call ARIMAResult.summary(), I see the estimated parameters, one of them being the variance of the error term.
Is there a way to get a probability density for each observation in my time series, assuming that it is generated by my estimated model?
I have looked through the documentation and have only found functions that give me the likelihood of my parameters but could not find anything for the probability of the series. I see that I can calculate what I want by using ARIMAResult.resid and the estimated variance. But why is there no built-in function for this?