Moshe Olshansky m_olshansky at yahoo.com writes:
Hi Misha,
Since PCA is a linear procedure and you have only 6000 observations, you do
not need 68000 variables. Using
any 6000 of your variables so that the resulting 6000x6000 matrix is
non-singular will do. You can choose
these 6000
-0700 (PDT)
From: misha680 mk144...@bcm.edu
Subject: [R] Principle components analysis on a large dataset
To: r-help@r-project.org
Message-ID: 25072510.p...@talk.nabble.com
Content-Type: text/plain; charset=us-ascii
Dear Sirs:
Please pardon me I am very new to R. I have been using MATLAB.
I
mk144...@bcm.edu wrote:
From: misha680 mk144...@bcm.edu
Subject: [R] Principle components analysis on a large dataset
To: r-help@r-project.org
Received: Friday, 21 August, 2009, 10:45 AM
Dear Sirs:
Please pardon me I am very new to R. I have been using
MATLAB.
I was wondering if R
Dear Sirs:
Please pardon me I am very new to R. I have been using MATLAB.
I was wondering if R would allow me to do principal components analysis on a
very large
dataset.
Specifically, our dataset has 68800 variables and around 6000 observations.
Matlab gives out of memory errors. I have tried
analysis on a large dataset
To: r-help@r-project.org
Received: Friday, 21 August, 2009, 10:45 AM
Dear Sirs:
Please pardon me I am very new to R. I have been using
MATLAB.
I was wondering if R would allow me to do principal
components analysis on a
very large
dataset.
Specifically
Dear Sirs:
Please pardon me I am very new to R. I have been using MATLAB.
I was wondering if R would allow me to do principal components analysis on a
very large
dataset.
Specifically, our dataset has 68800 variables and around 6000 observations.
Matlab gives out of memory errors. I have tried
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