-------- Original Message --------
Subject: Re: more CVA and LDF
Date: Fri, 17 Oct 2008 18:15:15 -0700 (PDT)
From: Paul Sanfilippo <[EMAIL PROTECTED]>
To: [email protected]
References: <[EMAIL PROTECTED]>
I'm also keen to hear any discussion about the differences between these
two methods and also how to perform particularly a CVA in R. I've used
the 'lda' function with cross-validation on a dataset which I think is
giving me the information I want, but how do you perform a CVA, Fabio
(or anyone else)?
On a side note to R (which I've been using a bit lately and am finding I
quite like, as steep as the learning curve is), has anyone read a book
called 'Morphometrics with R' by Julien Claude? I'm mainly interested in
learning how to use R to perform various statistical techniques once the
data has been analysed with the various other GMM software, so I don't
know how applicable this book is for me.
Thanks,
Paul Sanfilippo
Uni Melbourne
Australia
On Fri, Oct 17, 2008 at 8:41 PM, morphmet
<[EMAIL PROTECTED]
<mailto:[EMAIL PROTECTED]>> wrote:
-------- Original Message --------
Subject: more CVA and LDF
Date: Fri, 17 Oct 2008 01:59:31 -0700 (PDT)
From: Fabio de Andrade Machado <[EMAIL PROTECTED]
<mailto:[EMAIL PROTECTED]>>
To: [email protected] <mailto:[email protected]>
Hi all,
Sorry to bring this up once more, but I don´t think any response on
that have been posted (recently) on the list.
What are the key differences of Canonical Variate Analysis and Linear
Discriminant Functions?
On Pete E. Lestrel´s "Morphometrics for the Life Science" it reads "A
discriminant function is a linear equation, one per individual
specimen, derived from the set of original variables x1, x2, x3, ....,
xn, each of which is multiplied by a 'weighting' coefficient,
a1,a2,a3,...,an (...). A set of these discriminant functions (...) is
then computed for each individual case. Each discriminant function
score is orthogonal with respect to all others". (p. 159-160)
About Canonical Variate Analysis he says that it is design to
calculate "[1](...) the correlation between two derived variables and
[2] a set of canonical variates or canonical functions (as suns of
weighted variables)(...)" (p.161).
About both he says "Although displayed results are indistinguishable
in many respects, the purpose are different" (p.160), being the CVA
basically an graphical aid for LDF.
Can anyone send some references on the specifics of each method? They
seem distinct somehow. On R there are two different functions, being
the one associated with CVA basically for graphical purposes (which is
confusing, as the one can display graphically the results of
discriminant functions and they seem basically the same).
cheers,
--
Fabio de Andrade Machado
Laboratorio de Herpetologia/Morfometria
Museu de Zoologia da USP
Av. Nazaré, 481, Ipiranga
São Paulo, SP, 04263-000
Brazil
+55 11 61658120
+55 11 82631029
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Replies will be sent to the list.
For more information visit http://www.morphometrics.org
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For more information visit http://www.morphometrics.org
