On Jan 5, 2011, at 5:24 PM, Benjamin Polidore wrote:
I'm trying to identify patterns among various "paths" like the
following:
http://i.imgur.com/bQPI3.png
If I plot these, I can observe intuitively two different patterns: a
front
loaded (1 and 3) and a backloaded (2,4) progress path:
http://i.imgur.com/L5qwZ.png
I have thousands of observations like the above table, and I want to
use R
to identify clusters of these paths. I looked at spatstat, but it
seems
more relevant to points than paths.
You need some sort of distance measure. Perhaps get signed maximum
deviation from a diagonal progress = (1:13)/13, Or you could classify
by how wavy they were with max(dev.positive) - min(dev.negative)
Or for a two-D measure, you could divide the bin x Percentage space
into boxes and see which ones get entered. progress1 and progress 2
might enter mostly the digoanl boxes while progress 3 and 4 would be
in the lower-right-hand corner. If you gave the boxes associated
measures you could transform a trajectory back to the max(measure)
paradigm.
Alas, as I think about the possibilities I am reminded that the set of
possible functions on the interval [0, 1] is infinite. But perhaps
some sort of functional data analysis approach can put the pieces of
my dashed hopes back together. Come to think of it, there _is_ an fda
package:
http://www.psych.mcgill.ca/misc/fda/
--
David Winsemius, MD
West Hartford, CT
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