thank you john.
however, I am finding it difficult to automate on a matrix.
Pardon my ignorance in R computing:
I do not know how to automate on a matrix.
If I do the following it works:
> x = cor.test(d6[1,],d6[2,])
> x
Pearson's product-moment correlation
data: d6[1, ] and d6[2, ]
t = 10.5196, df = 10, p-value = 9.973e-07
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.8520623 0.9883592
sample estimates:
cor
0.9576655
If I want to run it on all rows, I do not know how to do it.
I tried following,
> lapply(d6,cor.test)
Error in cor.test.default(X[[1L]], ...) :
element 1 is empty;
the part of the args list of 'length' being evaluated was:
(y)
> sapply(d6,cor.test)
Error in cor.test.default(X[[1L]], ...) :
element 1 is empty;
the part of the args list of 'length' being evaluated was:
(y)
> for(i in 1:14659){
+ k = i+1
+ cor.test(d6[i,],d6[k,])
+ x = cor.test(d6[i,],d6[k,])
+ return(x)}
Error: no function to return from, jumping to top level
I appreciate your help.
thank you.
Adrian
On Sun, Sep 20, 2009 at 6:17 PM, Adrian Johnson
<oriolebaltim...@gmail.com> wrote:
> thank you john.
> however, I am finding it difficult to automate on a matrix.
>
> Pardon my ignorance in R computing:
>
> I do not know how to automate on a matrix.
>
> If I do the following it works:
>> x = cor.test(d6[1,],d6[2,])
>> x
>
> Pearson's product-moment correlation
>
> data: d6[1, ] and d6[2, ]
> t = 10.5196, df = 10, p-value = 9.973e-07
> alternative hypothesis: true correlation is not equal to 0
> 95 percent confidence interval:
> 0.8520623 0.9883592
> sample estimates:
> cor
> 0.9576655
>
>
> If I want to run it on all rows, I do not know how to do it.
>
> I tried following,
>
>> lapply(d6,cor.test)
> Error in cor.test.default(X[[1L]], ...) :
> element 1 is empty;
> the part of the args list of 'length' being evaluated was:
> (y)
>
>
>> sapply(d6,cor.test)
> Error in cor.test.default(X[[1L]], ...) :
> element 1 is empty;
> the part of the args list of 'length' being evaluated was:
> (y)
>
>> for(i in 1:14659){
> + k = i+1
> + cor.test(d6[i,],d6[k,])
> + x = cor.test(d6[i,],d6[k,])
> + return(x)}
> Error: no function to return from, jumping to top level
>
>
> I appreciate your help.
>
> thank you.
> Adrian
>
>
>
>
>
>
> On Sun, Sep 20, 2009 at 5:13 PM, John Kane <jrkrid...@yahoo.ca> wrote:
>> ?cor
>> ?cor.test
>>
>> --- On Sun, 9/20/09, Adrian Johnson <oriolebaltim...@gmail.com> wrote:
>>
>>> From: Adrian Johnson <oriolebaltim...@gmail.com>
>>> Subject: [R] correlation help
>>> To: r-help@r-project.org
>>> Received: Sunday, September 20, 2009, 5:00 PM
>>> Dear group,
>>>
>>> I have a matrix like the following:
>>>
>>> Name Sample1
>>> sample2 sample3 sample4 .....
>>> sample(n)
>>> nm1 10.5
>>> 13.5
>>> 30 31
>>> nm2 8
>>> 11
>>> 34
>>> 29
>>> nm3 9
>>> 10.3
>>> 27.8 35
>>> nm(j)
>>>
>>>
>>> I want to be able to calculate correlation between
>>> all pairs of names.
>>> For example (nm1,nm2), (nm1,nm3), (nm1,nmj), (nm2,nm3),
>>> (nm2,nmj)....
>>>
>>> Then I want to calculate the significance of correlation
>>> using t-score
>>> or p-value.
>>>
>>> I can calculate correlation coeffecient in excel but not
>>> significance
>>> in both excel and R.
>>>
>>> I want to be able to do it in R, I appreciate your help.
>>> thank you.
>>> Ad.
>>>
>>> ______________________________________________
>>> R-help@r-project.org
>>> mailing list
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>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained,
>>> reproducible code.
>>>
>>
>>
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