I fit a model to a series with
arima() in R with ARMA(5,5) and regression on some covariates.
fit5 = arima(x, order=c(5,0,5), xreg=covaraites, include.mean=F)
I am now checking if the fitted model is adequate. The residual series looks like:
The residual series pass the Ljung Box test with a p value 0.3859. The ACF and PACF of the residual series are as follows (seems it is uncorrelated, right?):
The qqplot for the residual series is as follows:
qqnorm(fit5$residuals, asp = 1) qqline(fit5$residuals, asp=1)
It looks okay within (-2, 2). I wonder if it is not okay to be Gaussian?
IIC, arma model requires its residual series to be a white noise but not necessarily Gaussian. But
arima() fits the model using MLE (assuming Gaussian residual series?). So if my residual series can't be taken as Gaussian, how shall I revise my model and what function in R I can use to fit to my time series?