This is really the same question, and a question posed
to you earlier about how why you think this would make sense
has not been answered.
However, we see here some (or perhaps all) of the data.
x takes one of two values, so your data are from a
discrete distribution. I think it difficult to see why an AR model would
be appropriate here. Possibly a Markov chain, which is loosely equivalent,
would make more sense.
There are 4 values of 0 and 4 values of 1 in this sample. Thus
the data are symmetrically distributed. No one-to-one
transformation that I could think of appears either necessary
or useful in this circumstance.
If these really are all the data, you are also challenged on
the score of sample size.
Nick
[email protected]
[email protected]
> thanks for response,and sorry for ambiguity
> here is the sample data:
> yearid x
> 1 1
> 2 1
> 3 0
> 4 1
> 5 0
> 6 0
> 7 0
> 8 1
>
> then, I want to apply AR for x. is that allowed? since x is
> variable only with
> value 1 and 0. if not, is there any transformation on x that
> we can do?
> Is that clear enough? thanks
Marcello Pagano <[email protected]>:
> > The reason, Tang, why there was not much of a response to your
> > question is that it is not possible to understand what your question
> > is. Of course, one can do AR on any variable, but the interpretation
> > might be a little challenging!
> > Please give us more details about your problem, otherwise don't post
> > again, please.
> >
[email protected]
> > >>can i do AR on a dummy variable? what do i need to do to
> transform the
> > >>variable.
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