----- Forwarded message from
[email protected] -----
Date: Wed, 05 Feb 2014
22:34:53 -0800
From: [email protected]
Reply-To: [email protected]
Subject: RE: Combining
geometric and traditional morphometric datasets
To:
[email protected]
----- Forwarded message from "F. James Rohlf"
<[email protected]> -----
Date: Sat, 1 Feb 2014
13:44:48 -0500
From: "F. James Rohlf"
<[email protected]>
Reply-To:
[email protected]
Subject: RE: Combining geometric and
traditional morphometric datasets
To:
[email protected]
My tpsPLS software is designed for such data. Download it at
http://life.bio.sunysb.edu/morph/soft-tps.html
- - - - - - - - - - - - - - - - - - - - - - - - - - - - -
F. James Rohlf, Distinguished Professor, Emeritus, Stony Brook University
The much revised 4th editions of Biometry and Statistical Tables are now available:
http://www.whfreeman.com/Catalog/product/biometry-fourthedition-sokal
http://www.whfreeman.com/Catalog/product/statisticaltables-fourthedition-rohlf
From: [email protected]
[mailto:[email protected]]
Sent: Friday, January
31, 2014 6:29 PM
To: [email protected]
Subject:
Combining geometric and traditional morphometric
datasets
----- Forwarded message from Kara
Feilich <[email protected]> -----
Date: Fri, 17 Jan 2014
16:22:49 -0500
From: Kara Feilich <[email protected]>
Reply-To: Kara Feilich <[email protected]>
Subject: Combining geometric and
traditional morphometric datasets
To: [email protected]
Hi all,
I'm fairly new at this, so I hope this question
makes sense:
I'm trying to look for covariation and/or modularity among
four datasets (all taken from the same individuals, with a phylogeny), where one
dataset has Procrustes coordinates for body landmarks, and the other datasets
use linear measures. Is there a way to look for (even just two-way) covariation
among the datasets? I would like to use a partial least squares approach, but
I'm not sure if the single dimension linear measures will play with the two
dimensional landmarks.
Though, if the landmark coordinates are broken
down so that the x and y components of the coordinates are considered
independent (i.e. if you have 10 landmarks, it's considered 20 variables), I
should be able to just append linear measures as long as I consider them a
separate partition, maybe? I hope?
Any ideas on how to work with
geometric and traditional measures in tandem would be greatly
appreciated.
Thanks,
Kara
_______
Kara
Feilich
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