Re: Correlation matrix is not positive definite

Posted by Art Kendall on Nov 28, 2011; 1:04pm
URL: http://spssx-discussion.165.s1.nabble.com/Correlation-matrix-is-not-positive-definite-tp4999980p5028829.html

Our research purpose is to distinguish different bacteria from their
fluorescence emission spectra.

Then shouldn't kinds of bacteria be a variable in the model?  Is that your independent variable?

I am trying to get a handle on your design (model).
You  have 1 dependent variable -- intensity of fluorescence emission.  It is repeatedly measured  along a spectrum of wavelengths.  The repeats are at 1nm interval. Repeats are an independent (i.e., design) variable).
This is the same as time series except that the increments are of wavelength rather than time.

Is there only one value for the the stimulus to excite the fluorescence?

Many uses of spectra (repeated measures across a spectrum like time or wavelength) are to find or compare profiles.  Is this perhaps what you want to do?

Are you trying to find out if different bacteria have different profiles?  Do you have pre-identified groups of bacteria and want to know how their profiles can be discriminated from each other?
Or are you trying to find sets of profiles that are maximally similar with the set and maximally different between the sets?

I hope we are getting closer to understanding your underlying question.

Art Kendall
Social Research Consultants




On 11/28/2011 2:06 AM, viswa21 wrote:

Hi Art,
             The data was obtained using fluoro-spectrometer.

Our research purpose is to distinguish different bacteria from their
fluorescence emission spectra. The emission spectrum is continuous from
260-430nm with 1nm increment. independent variable is wavelength and
dependent variable is intensity of emitted light from bacteria.

So there might be many variables whose values are similar with each other,
that is why the correlation matrix is not positive definite.

Now my question is how to choose important variable?? in other words which
variables should i leave in data matrix, so that data matrix be reduced
(with less no. of variables) and becomes positive definite and it lets us to
carry out PCA which makes sense??

Please suggest me further... i need resolve this issue ASAP.
Thanks
Regards
Visu

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