Hi Jonathan,

I don't know if I got the point, but for thresholds assessments, give a look
at segmented package.

bests
milton
brazil=toronto

On Tue, Jun 16, 2009 at 5:23 PM, Jonathan Greenberg
<greenberg@ucdavis.edu>wrote:

> Rers:
>
> I have some ecological data (stream velocity vs. % cover of submerged
> weeds) that shows strong evidence of a thresholding step-function, e.g.
> below some velocity, % cover ranges from 0% to 100% (with no apparent
> relationship to velocity within this range of velocities), but above a
> certain "threshold" velocity, the % cover does not appear to exceed, say,
> 10%.  There are good mechanistic reasons for believing there is a step
> function there, so I'm trying to determine the velocity position and
> significance of this threshold.  I came up with the following approach, but
> I was hoping to find out if there is a more "standardized" way of doing
> this:
>
> 1) Give small velocity steps ranging from 0 to max velocity,  classify all
> samples (% cover vs. velocity) into "above threshold" and "below threshold".
> 2) Perform a t-test on these two groups, store the p-value to an array,
> building up a database of p-value vs. velocity threshold.
> 3) Determine the minimum p-value from the previous step, which should be
> the velocity threshold -- the p-value at this threshold is the significance
> of the threshold.
>
> Does this make sense?  Is there a better way of doing this?  When I ran
> this on the data, you see a nice, nearly parabolic relationship around what
> the threshold appears to be of p-value vs. threshold.
>
> --j
>
> --
>
> Jonathan A. Greenberg, PhD
> Postdoctoral Scholar
> Center for Spatial Technologies and Remote Sensing (CSTARS)
> University of California, Davis
> One Shields Avenue
> The Barn, Room 250N
> Davis, CA 95616
> Cell: 415-794-5043
> AIM: jgrn307, MSN: jgrn307@hotmail.com, Gchat: jgrn307
>
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