| Re: does principle component=Factor analysis? [message #59421] |
Thu, 27 March 2008 11:18  |
David Fanning
Messages: 11724
Registered: August 2001
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Senior Member |
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d.poreh@gmail.com writes:
> i am using principle component for some remotly sensed data
> (classification). I hear we can do this by factor analysis too. does
> anybody know this is a same thing or not?
I guess Coyote got bored waiting for the mailman to show
up with the next Girls Gone Wild video from Netflix, but
he tells me he spent the whole morning researching this
extensively on the Web. The answer, apparently is
"Yeah, sorta."
Cheers,
David
--
David Fanning, Ph.D.
Fanning Software Consulting, Inc.
Coyote's Guide to IDL Programming: http://www.dfanning.com/
Sepore ma de ni thui. ("Perhaps thou speakest truth.")
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| Re: does principle component=Factor analysis? [message #59520 is a reply to message #59421] |
Thu, 27 March 2008 12:23  |
Jean H.
Messages: 472
Registered: July 2006
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Senior Member |
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> I guess Coyote got bored waiting for the mailman to show
> up with the next Girls Gone Wild video from Netflix, but
> he tells me he spent the whole morning researching this
> extensively on the Web. The answer, apparently is
> "Yeah, sorta."
>
> Cheers,
>
> David
Factor analysis is a statistical method used to explain variability
among observed random variables in terms of fewer unobserved random
variables called factors. The observed variables are modeled as linear
combinations of the factors, plus "error" terms. The information gained
about the interdependencies can be used later to reduce the set of
variables in a dataset. Factor analysis originated in psychometrics, and
is used in behavioral sciences, social sciences, marketing, product
management, operations research, and other applied sciences that deal
with large quantities of data.
Factor analysis is often confused with principal components analysis.
The two methods are related, but distinct, though factor analysis
becomes essentially equivalent to principal components analysis if the
"errors" in the factor analysis model are assumed to all have the same
variance.
http://en.wikipedia.org/wiki/Factor_analysis
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