Distance matrix based on correlation coefficient

I would much appreciate if someone would enlighten me on how to calculate a 
distance matrix based on correlation coefficient (Spearman)? The simple 
correlation matrix seems not to work.

In what sense did it not work? We aren't mind readers! Hence the posting
guide asking you to provide information that will help us to help you.

I am trying to use it in FSO/MFSO to calculate the influence of 
climate factors on heavy metals concentrations.

Does this help at all?

dat <- data.frame(A = rnorm(10), B = rnorm(10), C = rnorm(10))
cor(dat)

A          B         C
A 1.00000000 0.08986947 0.1224007
B 0.08986947 1.00000000 0.2667838
C 0.12240068 0.26678381 1.0000000

1 - cor(dat) ## dissimilarity

A         B         C
A 0.0000000 0.9101305 0.8775993
B 0.9101305 0.0000000 0.7332162
C 0.8775993 0.7332162 0.0000000

as.dist(1 - cor(dat))

A         B
B 0.9101305          
C 0.8775993 0.7332162

HTH

G

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 Dr. Gavin Simpson             [t] +44 (0)20 7679 0522
 ECRC, UCL Geography,          [f] +44 (0)20 7679 0565
 Pearson Building,             [e] gavin.simpsonATNOSPAMucl.ac.uk
 Gower Street, London          [w] http://www.ucl.ac.uk/~ucfagls/
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