Friends

I am new to R (and statistics) so am struggling a bit.

Briefly...

I am interested in getting the P-Value from cor(X) where X is a matrix.

I have found cor.test.

Verbosely...

I have 4 vectors and can generate the corellation matrix...


> cor(cbind(X1, X2, X3, X4))
       X1       X2       X3       X4
X1 1.00000000 -0.06190365 -0.156972795 0.182547517
X2 -0.06190365 1.00000000 0.264352860 0.146750844
X3 -0.15697279 0.26435286 1.000000000 -0.006380052
X4 0.18254752 0.14675084 -0.006380052 1.000000000

But I want the P-Values (gives me the significance I belive).

> cor.test(X2, X3)

 Pearson's product-moment correlation

data: X2 and X3
t = 3.3346, df = 148, p-value = 0.001080
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.1086963 0.4073565
sample estimates:
   cor
0.2643529

is very cool. Just what I want. But there is too much information for
too little data.

What I would like to do is some thing like...

cor_with_p_test(cbind(X1, X2, X3, X4))
  X1       X2         X3
X1   1       -0.06190365    -0.1569728...
P           0.4517       0.05507  ...

X2 -0.06190365 1           0.2643529 ...
P  0.4517                0.001080 ...
:
:

I think I could write a function for it if such a function does not exist
if I could do...

> CT23 <- cor.test(X2, X3)
> CT23$P
0.001080
> CT23$V
0.2643529

But I do not know how.

cheers
Worik

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