Hi Brett,
I don't know what you want to do using generalized inverse matrices.
Is it a two sample comparison? These two references give everything you
need to know to defend the singular value decomposition type generalized
inverses.
http://www.uwlax.edu/faculty/will/svd/index.html
http://www.snl.salk.edu/~shlens/pub/notes/pca.pdf
Best regards,
Ben Flood
-----Original Message-----
From: morphmet [mailto:[EMAIL PROTECTED]
Sent: 16 March 2005 14:27
To: morphmet
Subject: generalised inverse matrices
Hello All,
I am having issues with singular matrices because the number of variables
(linear morphometric measures) I have far exceeds the number of samples. I
don't wish to introduce a bias into my analyses by selecting variables to
include/exclude from my data matrix, hence I am wondering about the validity
of using generalised inverse matrices.
Is the use of generalised inverse matrices a valid/ accepted one?
Are generalised inverse matrices statistically robust and will people
believe my results?
Has anyone published using generalised inverse matrices?
How would I defend the use of generalised inverse matrices?
Thanks in advance,
Brett Human
************************
Brett Human, PhD
Shark Researcher
27 Southern Ave
West Beach SA 5024
Australia
Ph: +61 8 8356 6891
email: [EMAIL PROTECTED]
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