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In time series analysis, the moving-average (MA) model is a common approach for modeling univariate time series. The moving-average model specifies that the output variable depends linearly on the current and various past values of a stochastic (imperfectly predictable) term.

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Determining the numerical value of the parameters of a Moving Average process

Is it possible to determine the numerical value of the parameters of a moving average process just by looking at the correlogram (Autocorrelation function and Partial Autocorrelation function) of the …
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1 vote

Determining the numerical value of the parameters of a Moving Average process

I computed the correlation between $y_{t}$ and $y_{t-1}$ as follows: \begin{equation} Cov(y_{t}, y_{t-1})=E[y_{t}y_{t-1}]-E[y_{t}]E[y_{t-1}]=E[y_{t}y_{t-1}] = E[(\epsilon_{t}+\alpha \epsilon_{t-1})(\e …
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