I am currently working with ARIMA models and I am a little confused about the way they are formulated. I found Rob J. Hyndman's blog post "Constants and ARIMA models in R" explaining it.
But still, I'm confused. I am looking to fit an ARIMA(1,2,1) model to my dataset, $y_t$ for $t=1,...,n$. I gather from the website that it takes the form
$$(1-\phi B)(1-B)^2y_t=\mu(1-\phi)+(1+\theta B)\varepsilon_t$$
with $\mu$ being the mean of $(1-B)^2y_t$, that is the mean of
I guess I don't understand which $y_t$'s we need to take the mean of. Is it those of our dataset? Or if otherwise $y_t$ would depend on $y_t$ itself which does not make much sense.