Message-ID: <CAB8pepwqjytOC20AxRn6W9pSeAvQjyTcfqe=Y7V6B4PjiYxDnA@mail.gmail.com>
Date: 2019-05-15T04:00:49Z
From: Abby Spurdle
Subject: Different predictions with forecast::auto.arima()
In-Reply-To: <6074A4D9-E7EF-47BB-9706-366789557282@dcn.davis.ca.us>
> This is definitely a statistics question still so not on topic here... as
changing the data is exactly the kind of thing that can have this effect.
I'm sorry.
I disagree.
This is a question about reproducible code.
So, I don't see why it should be considered off topic.
> >The function returned a (2,1,0) model with drift. However when I used the
> >same function it returns a (1,1,0) model. There were no obvious
differences
> >in the code. The only thing passed to it was the data. How might this
> >happen?
Either a different version of R, a difference in the forecast package, a
difference in one of it's imports (which there are many), or different
input.
If you're sure the input is the same, then it must be one of the other
reasons.
I suggest reading the documentation for the relevant forecast package
functions.
The auto.arima() function alone has many arguments.
Changing their values may produce a more desirable model.
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