Question

Differentiate between the autoregressive and moving average models of time series.

08 Sep 2023
Answer :
Word Count : 875

TRUE

Autoregressive (AR) and Moving Average (MA) models are two fundamental approaches in time series analysis. They differ in how they model and capture temporal dependencies within a time series. Here is a differentiation between the two:

  1. Definition:

    • Autoregressive (AR) Model: AR models use past values of the time series itself to predict future values. They assume that the current value of the time series is a linear combination of its past values and a white noise error term.
    • Moving Average (MA) Model: MA models use past forecast errors (residuals) to predict future values. They assume that the current value of the time series is a linear combination of past forecast errors and a white noise error term.

  2. Mathematical Representation:

    • AR Model (AR(p)): y(t) = c + φ1y(t-1) + φ2y(t-2) + ... + φp*y(t-p) + ε(t)
    • MA Model (MA(q)): y(t) = c + θ1ε(t-1) + θ2ε(t-2) + ... + θq*ε(t-q) + ε(t)

  3. Parameters:

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