Path: news.mathworks.com!not-for-mail
From: <HIDDEN>
Newsgroups: comp.soft-sys.matlab
Subject: Re: SVD with Missing Values
Date: Fri, 5 Dec 2008 01:39:02 +0000 (UTC)
Organization: The MathWorks, Inc.
Lines: 15
Message-ID: <gha0nm$773$1@fred.mathworks.com>
References: <gh7kvc$anh$1@fred.mathworks.com> <07963786-05dd-4dde-8381-fb56604d2ea8@k36g2000pri.googlegroups.com>
Reply-To: <HIDDEN>
NNTP-Posting-Host: webapp-05-blr.mathworks.com
Content-Type: text/plain; charset="ISO-8859-1"
Content-Transfer-Encoding: 8bit
X-Trace: fred.mathworks.com 1228441142 7395 172.30.248.35 (5 Dec 2008 01:39:02 GMT)
X-Complaints-To: news@mathworks.com
NNTP-Posting-Date: Fri, 5 Dec 2008 01:39:02 +0000 (UTC)
X-Newsreader: MATLAB Central Newsreader 1626144
Xref: news.mathworks.com comp.soft-sys.matlab:505096


BHUPALA <bhupala@gmail.com> wrote in message <07963786-05dd-4dde-8381-fb56604d2ea8@k36g2000pri.googlegroups.com>...
> On Dec 4, 9:06=A0am, "Samuel " <sdods...@jhu.edu> wrote:
> > In MATLAB, what is the best way to handle a single value decomposition wh=
> ere k is much less then m or n (MxN matrix) for a data set with many missin=
> g values such that the missing values have a minimal effect on the decompos=
> ition. Thanks.
> 
> Try using svd(X,0) or svd(X,'econ')  which will give you economy
> singular values.
> 
> bhupala

The matrix for reference is 241x241 so an economy SVD won't do the trick. I'm looking for an alternative to mean imputation for the missing values. Is there any method I can use where I can treat the values as true unknown NaN values.