适合ARIMA模型的时间序列的方差

Question

I think this is a basic question, but maybe I am confusing the concepts.

Suppose I fit an ARIMA model to a time series using, for example, the function auto.arima() in the R forecast package. The model assumes constant variance. How do I obtain that variance? Is it the variance of the residuals?

If I use the model for forecasting, I know that it gives me the conditional mean. I'd like to know the (constant) variance as well.

Thank you.

Bruno

Answer 1

from the arima() help I see

sigma2  
  the MLE of the innovations variance.

var.coef    
  the estimated variance matrix of the 
  coefficients coef, which can be extracted 
  by the vcov method.

It seems like which you want will depend on your model. I am pretty sure you want sigma2.

to get the sigma2 do:

?arima
x=cumsum(rcauchy(1000))

aax=auto.arima(x)
str(aax)
aax$sigma2