-------- Original Message --------
Subject: more CVA and LDF
Date: Fri, 17 Oct 2008 01:59:31 -0700 (PDT)
From: Fabio de Andrade Machado <[EMAIL PROTECTED]>
To: [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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