Can a gaussian ARMA process have non-gaussian innovations? (i.e., is there an ARMA process that is gaussian, but the corresponding innovations are not gaussian)?
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If a process is Gaussian, then any linear combination of its elements is Gaussian too. Take for example the AR(1) process: $$X_t=\phi X_{t-1}+\varepsilon_t$$ Then $$\varepsilon_t=X_t-\phi X_{t-1},$$ i.e. the innovation is a linear combination of the process elements, hence it should be Gaussian if $\{X_t\}$ is Gaussian. |
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Alternatively you could check out literatures on Generalized Autoregressive Moving Average Model (GARMA), which extend univariate ARMA models to non-Gaussian situations, which extends the Generalized Linear Modelds (exponential family distributions) to incoproate time dependence in the observations. I assume this is what you are interested. Gaussian ARMA is with Gaussian error process, but in GARMA you can assume non-Gaussian distributions in the error process. |
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