Physically understanding autoregressive model (really basic question)

1. How do you interpret autoregressive model results?
2. How will you determine the order of an autoregressive process?
3. What are the parameters of AR model?
4. What is the difference between autoregressive and moving average?

How do you interpret autoregressive model results?

You can interpret it as the part of the previous value which remains in the future. It's good to note that these coefficients should always be between -1 and 1. Let me explain why. If the absolute value of the coefficient is greater than 1, then over time, it would blow up immeasurably.

How will you determine the order of an autoregressive process?

The order of an autoregression is the number of immediately preceding values in the series that are used to predict the value at the present time. So, the preceding model is a first-order autoregression, written as AR(1).

What are the parameters of AR model?

The AR parameters can be estimated using several techniques such as Kalman filter, Yule-Walker, Expectation-Maximization, least-square, Burg, forward-backward algorithm, etc. [49,180–183][49][180][181][182][183].

What is the difference between autoregressive and moving average?

A Moving Average model is similar to an Autoregressive model, except that instead of being a linear combination of past time series values, it is a linear combination of the past white noise terms.