Re: CV shape variation

Sun, 03 Jun 2012 23:04:38 -0700


----- Forwarded message from Philipp Mitteröcker -----

Date: Fri, 1 Jun 2012 05:52:44 -0400
From: Philipp Mitteröcker
Reply-To: Philipp Mitteröcker
Subject: Re: CV shape variation
To: [email protected]

For a single canonical variate, you can compute the variance along this CV and divide it by the total variance (computed, e.g., as the sum of the variances of all variables). But in contrast to PCA, you cannot add up the variances for two or more CVs, because the CV axes are not orthogonal. You could compute the variance within the plane spanned by two CVs when orthogonalizing the two CV axes.
However, explained variance among the individuals is not often reported for CVA, as it is not the quantity that is maximized.

Best,

Philipp 




Am 01.06.2012 um 06:27 schrieb [email protected]:


----- Forwarded message from beatriz gamarra -----

Date: Wed, 30 May 2012 13:29:58 -0400
From: beatriz gamarra 
Reply-To: beatriz gamarra 
Subject: CV shape variation
To: [email protected]

Hi,
I am analyzing a dataset with 12 landmarks and 12 groups. I have run CVA by using CVAGen6 from IMP and I want to obtain the shape variation associated with first CVs. How could I achieve?
Thanks in advance.

Beatriz Gamarra


----- End forwarded message -----





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Dr. Philipp Mitteroecker

Department of Theoretical Biology
University of Vienna
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A-1090 Vienna, Austria

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email: [email protected]
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