On 31/08/2010 11:00 AM, David Winsemius wrote:
On Aug 31, 2010, at 10:35 AM, <murali.me...@avivainvestors.com> <murali.me...@avivainvestors.com
> wrote:
> Hi Duncan,
>
> Thanks for your response.
>
> Indeed, independent normal errors were what I had in mind. As for
> variances, if I assume they are the same, would a 'pooled model'
> apply in this case? Is that equivalent to your suggestion of
> concatenating x(1,t) and x(2,t)?
>
Wouldn't this be equivalent to a segmented regression analysis that
would estimate the slopes in the two periods as mu(1) and mu(2), throw-
away any level shift estimate at the join-point, and which then
estimated the residual one-lag autocorrelation (again omitting the
join point) and assigned that value to "d"?
That is a different model. In the given situation, successive
observations are correlated, so if x(1, t) had a large residual above
the line, x(1, t+1) would be expected to have a large residual as well,
and as long as |d-1| is less than 1, the given model would have zero
slope in the long run.
Duncan Murdoch
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