| Re: Principal component analysis [message #57324 is a reply to message #57151] |
Wed, 05 December 2007 08:57  |
Vince Hradil
Messages: 574
Registered: December 1999
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Senior Member |
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On Dec 5, 10:47 am, "Haje Korth" <haje.ko...@nospam.jhuapl.edu> wrote:
> Yup, that'll do it. I am still not sure I understand the logic behind this.
> I though the correlation is part of the PCA.
>
> "Vince Hradil" <hrad...@yahoo.com> wrote in message
>
> news:8362380a-217a-45d2-b7c4-0198e5931b39@y5g2000hsf.googleg roups.com...
>
>> On Dec 5, 10:08 am, "Haje Korth" <haje.ko...@nospam.jhuapl.edu> wrote:
>>> I have tried that, it gives
>>> IDL> ev=imsl_princ_comp(correlate(a,/cov)) & print,ev
>>> 45.2906 3.70938-2.65683e-006
>
>>> These EVs are the same as you get using PCOMP with /COV keyword.
>
>>> "Vince Hradil" <hrad...@yahoo.com> wrote in message
>
>>> news:54fc6ed8-ccd7-4ac6-8e0d-09f5d190eeac@o6g2000hsd.googleg roups.com...
>
>>>> On Dec 5, 9:12 am, Vince Hradil <hrad...@yahoo.com> wrote:
>>>> > On Dec 5, 8:00 am, "Haje Korth" <haje.ko...@nospam.jhuapl.edu> wrote:
>
>>>> > > Hi,
>>>> > > I am puzzled by principal component analysis. I calculated the
>>>> > > eigenvalues
>>>> > > using both PCOMP and IMSP_PRINC_COMP routines. Could someone
>>>> > > enlighten
>>>> > > me
>>>> > > why the results are completely different? I have tried different
>>>> > > keywords to
>>>> > > see whether I can match them by trial and error, but I had no
>>>> > > success.
>>>> > > There
>>>> > > must be someone out there who undertstands this much better than I
>>>> > > do.
>
>>>> > > Thanks so much,
>>>> > > Haje
>
>>>> > > IDL> a=[[1,-2,-6],[-2,1,-3],[-6,-3,5]]
>>>> > > IDL> pca=pcomp(a,eigenvalues=ev) & print,transpose(ev)
>>>> > > 2.24227 0.757732 0.000000
>>>> > > IDL> ev=imsl_princ_comp(a) & print,ev
>>>> > > 9.53359 -5.19751 2.66392
>
>>>> > From the HELP:
>
>>>> > Syntax
>>>> > Result = IMSL_PRINC_COMP(covariances [, /COV_MATRIX]
>>>> > [, /CORR_MATRIX] [, CORRELATIONS=variable] [, CUM_PERCENT=variable] [,
>>>> > DF=variable] [, /DOUBLE] [, EIGENVECTORS=variable] [,
>>>> > STDEV=variable] )
>
>>>> > Note that IMSL_PRINC_COMP requires that you pass the covariance or
>>>> > correlation matrix - not the vectors.
>
>>>> so maybe try
>>>> ev=imsl_princ_comp(correlate(a,/covariance) & print, ev
>>>> (I don't have an analyst license)
>
>> There you go 8^)
>> How about
>> ev=imsl_princ_comp(correlate(a)) & print, ev
Oh, yes correlation IS part of PCA, it's just that IMSL decided to let
the user do that part him/herself. IMSL_PRINC_COMP calculates the
principal components of the cov/cor matrix. Calculating these
principal components is just part of "Principle Components Analysis".
IMSL leaves it up to the user to decide how to implement the principal
components in his/her analysis.
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