data structure problem

my situtation is that each data point is made up of p correlated 5-dimension
vectors. Those 5 dimensions are orthogonal.
Any suggestions will be appreciated!

JP


-----Original Message-----
From: Liaw, Andy [mailto:andy_liaw at merck.com]
Sent: Monday, January 12, 2004 10:00 PM
To: 'Jieping'; r-help at stat.math.ethz.ch
Subject: RE: [R] data structure problem


Without more information on the context of the data, it's hard to say much
that will be useful.

One possibility is to treat the 5*p entries as 5*p variables, and apply the
commonly available discriminant tools to that.  Given more information, it
might be possible to do better.  As an example, one data set that has been
used as benchmark is the scanned images of hand-written digits.  Each digit
is encoded in a k x k matrix of values expressing the grayscale level of
each pixel (don't remember what k is).  A straight-forward way to train a
algorithm for pattern recognition is to treat the data as having kxk
variables.  However, smarter (but custom-built, rather than off-the-shelf)
algorithms can make use of the fact that the data is actually an image, and
possibly get better results.

Cheers,
Andy

From: Jieping

HI, there,
   I have a data set with special structure.
   It is in n*(5*p): n is the number of observations or data points
                     5*p is the matrix for each data point
   I'd like to conduct discriminant analysis to this data
set. How could I
do? And where could I find related references to solve this problem?

Thanks a lot!


Jieping Zhao
PhD student in Bioinformatics, NCSU
Lab homepage: http://coltrane.gnets.ncsu.edu/index.html

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