I am new to Time Series Analysis and I have problems understanding the MA-model (opposed to the AR model). I read many webpages about it and it is either said that MA is a linear regression with past forecast errors or with white noises. So some label the Epsilons as past forecast errors and others as white noise.
My question is whether there is a difference between those two 'approaches'? Further, I do not understand how we can calculate the forecast errors. As far as I understood MA is used for forecasting itself. So how can I fit a forecasting model that itself relies on an forecast (of past error terms)? So my basic question is how can I calculate the Epsilon-parameters of the MA model?
I'd appreciate every comment.
EDIT: Do you know a website where the MA model is explained in an understandable ways also for people who have just started to learn and use time series? I still do not know how I can calculate the parameters.