"Ng Stanley" <[EMAIL PROTECTED]> wrote::
> Seeking suggestions to compute uncentered (pearson correlation)
> correlation efficiently.
>
> corr from stats library works on x and y columns. dist from amap
> library works on x and y rows.
>
> My data layout is slightly different such that row(i) of matrix x
> is compared to row(i) of matrix y.
Do you mean cor()?
> ?corr
No documentation for 'corr' in specified packages and libraries:
you could try 'help.search("corr")'
I do not think that cor() will complain when you send it rows rather than
columns.
r25 <- matrix(rnorm(25),ncol=5)
q25 <- matrix(rnorm(25),ncol=5)
> r25
[,1] [,2] [,3] [,4] [,5]
[1,] 0.9075305 0.1768761 0.9946014 -2.1863247 -1.4031437
[2,] -0.6675117 0.5282182 -0.2522370 -0.3905784 -1.7219424
[3,] 0.7975418 -0.1992466 0.8884690 2.4123639 -0.9834216
[4,] 0.4027469 1.7962510 -0.1084113 0.7382887 0.2165000
[5,] -1.3969290 1.3095061 0.8976753 0.5161417 -2.0408553
> cor(q25[,1],r25[,1])
[1] 0.4221951
> cor(q25[1,],r25[1,])
[1] -0.4903181
--
David Winsemius
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