Pradyumna S Upadrashta <[EMAIL PROTECTED]> wrote:

>Does anyone know of any (simple) papers that discuss the relationship
>between nonlinearity and long-autocorrelation times in time-series? Many
>times I have run across the suggestion that "long autocorrelation times"
>suggest nonlinear behavior, but aside from the clearly non-stationarity
>of such processes, what else can be said about long autocorrelation
>times?

I'm not particularly familiar with this area, and can't give you any
references, but I have a couple comments.

First, a time series with long autocorrelation times must be stationary.  
Autocorrelation time isn't defined for non-stationary series.  Of
course, a non-stationary series will often produce *estimates* for
autocorrelations that appear to correspond to a time series with long
autocorrelation time, but these are estimates for something that
doesn't actually exist.

Second, I don't see why long autocorrelation times would have any
particular relationship with nonlinearity - assuming that by the
latter, you mean a non-Gaussian joint distribution.  There is a
multivariate Gaussian distribution with any given correlation matrix.
There will also, of course, be many non-Gaussian distributions with
the same correlation matrix.

   Radford Neal

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Radford M. Neal                                       [EMAIL PROTECTED]
Dept. of Statistics and Dept. of Computer Science [EMAIL PROTECTED]
University of Toronto                     http://www.cs.utoronto.ca/~radford
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