If a time series process depends on its own past values then it's a AR process. These is what i understood but if it depends on it's own error then it's a MA process. Here is where i get confused.
Today = mean + Noise + slope(yesterday's error)
How these error got generated beforehand? Error is when a time series is forecasted using any forecasting model and then Actual - forecasted gives error.MA model regressed on these error.Is these the same error we consider in MA. If yes then how these error are generated first in MA?
I got stuck here.
Although got some nice references below one to be specific but not able to understand intuitively. Moving Average (MA) process: numerical intuition