Interface between fractal geometry and statistics

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Interface between fractal geometry and statistics

Ted Byers
Are there any packages that help with statistical analysis in situations where
fractal geometry is relevant?  Perhaps something that supports computation of
fractal related statistics, such as the Hurst exponent or fractal dimension?  
Or perhaps which support obvious tasks such as taking samples from a dataset
at different levels of granularity (such as sampling spatial data at cm, m, km
spatial resolution, or sampling daily time series at weekly, monthly, quaterly
or annual resolution)?

Thanks

Ted

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Re: Interface between fractal geometry and statistics

Spencer Graves
      RSiteSearch('fractal', 'fun') returned 68 hits for me just now.  
Might any of those be helpful?

      Spencer

Ted wrote:

> Are there any packages that help with statistical analysis in situations where
> fractal geometry is relevant?  Perhaps something that supports computation of
> fractal related statistics, such as the Hurst exponent or fractal dimension?  
> Or perhaps which support obvious tasks such as taking samples from a dataset
> at different levels of granularity (such as sampling spatial data at cm, m, km
> spatial resolution, or sampling daily time series at weekly, monthly, quaterly
> or annual resolution)?
>
> Thanks
>
> Ted
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>

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Re: Interface between fractal geometry and statistics

Antonio, Fabio Di Narzo
In reply to this post by Ted Byers
2008/7/4 Ted <[hidden email]>:
> Are there any packages that help with statistical analysis in situations where
> fractal geometry is relevant?  Perhaps something that supports computation of
> fractal related statistics, such as the Hurst exponent or fractal dimension?
tseriesChaos has functions for estimating correlation dimension on an
observed (long) time series.

> Or perhaps which support obvious tasks such as taking samples from a dataset
> at different levels of granularity (such as sampling spatial data at cm, m, km
> spatial resolution, or sampling daily time series at weekly, monthly, quaterly
> or annual resolution)?
For time series, look for 'aggregate'.

f.

>
> Thanks
>
> Ted
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>



--
Antonio, Fabio Di Narzo
Ph.D. student at
Department of Statistical Sciences
University of Bologna, Italy

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