Well if your matrix and vector are centered and properly scaled (and there are
no missing values), then the correlations are just a crossproduct and matrix
arithmetic is already fairly fast (assuming you have enough memory).
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of jastar
> Sent: Thursday, May 14, 2009 2:06 PM
> To: r-help at r-project.org
> Subject: [R] "Fast" correlation algorithm
>
>
> Hi,
> Is in R any "fast" algorithm for correlation?
> What I mean is:
> I have very large dataset (microarray) with 55000 rows and 100 columns.
> I
> want to count correlation (p-value and cor.coef) between each row of
> dataset
> and some vector (of course length of this vector is equal to number of
> columns of dataset).
> In short words:
> For t-test we have:
> "normal" algorithm - t.test
> "fast" algorithm - rowttests
> For correlation:
> "normal" algorithm - cor.test
> "fast" algorithm - ???
>
> Thank's for help
> --
> View this message in context: http://www.nabble.com/%22Fast%22-
> correlation-algorithm-tp23548016p23548016.html
> Sent from the R help mailing list archive at Nabble.com.
>
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