Have you consulted R's extensive documentation? -- in particular, "An
Introduction to R," which would seem like an obvious place for R
newbies to start. If you had done so, you would have found your
question answered there in section 6.1 on lists.
-- Bert Gunter
On Wed, Dec 22, 2010 at 9:39 AM, <govin...@msu.edu> wrote:
>
>
> Thank you both for your suggestions. I have another question - is there a
> specific way to access the individual elements of a 'list' variable? i.e.
>
> dmi = matrix(rnorm(20),4,5)
> soi = matrix(rnorm(20),4,5)
> pe = matrix(rnorm(20),4,5)
> y <- list(dmi, soi, pe)
>
> y[[1]] gives
> [,1] [,2] [,3] [,4] [,5]
> [1,] -0.54463900 1.6732445 -0.3807847 -1.0460530 -0.8142748
> [2,] -0.49654004 -0.9634258 0.9074139 -0.1576030 -1.2268558
> [3,] -1.61835766 -0.4240122 0.3626670 0.7182964 0.1576446
> [4,] -0.06313983 0.6743465 -1.9897107 0.8027337 -1.4372131
>
> But, I am interested in accessing the 1st column of 'dmi' matrix here - not
> as dmi[,1] but in terms of 'y'. Is it possible with 'list' function or
> something else?
>
> Thanks again.
>
> --
> Regards,
> Maha
> Graduate Student
> Department of Geography
> Michigan State University
> Quoting Liviu Andronic <landronim...@gmail.com>:
>
>> On Wed, Dec 22, 2010 at 2:57 AM, Phil Spector
>> <spec...@stat.berkeley.edu> wrote:
>>> To make your loop work, you need to learn about the get function.
>>> I'm not going to give you the details because there are better
>>> approaches available.
>>> First, let's make some data that will give values which can be verified.
>>> (All the correlations of the data you created
>>> are exactly equal to 1.) And to make the code readable, I'll
>>> omit the ts.m prefix.
>>>
>>>> set.seed(14)
>>>> dmi = matrix(rnorm(20),4,5)
>>>> soi = matrix(rnorm(20),4,5)
>>>> pe = matrix(rnorm(20),4,5)
>>>> allmats = list(dmi,soi,pe)
>>>
>>> Since cor.test won't automatically do the tests for all columns
>>> of a matrix, I'll write a little helper function:
>>>
>>>> gettests = function(x)apply(x,2,function(col)cor.test(pe[,2],col)
>>>> tests = lapply(allmats,gettests)
>>>
>>> Now tests is a list of length 2, with a list of the output from
>>> cor.test for the five columns of the each matrix with pe[,2]
>>> (Notice that in your program you made no provision to store the results
>>> anywhere.)
>>>
>>> Suppose you want the correlations:
>>>
>>>> sapply(tests,function(x)sapply(x,function(test)test$estimate))
>>>
>>> [,1] [,2]
>>> cor 0.12723615 0.1342751
>>> cor 0.07067819 0.6228158
>>> cor -0.28761533 0.6218661
>>> cor 0.83731828 -0.9602551
>>> cor -0.36050836 0.1170035
>>>
>>> The probabilities for the tests can be found similarly:
>>>
>>>> sapply(tests,function(x)sapply(x,function(test)test$p.value))
>>>
>>> [,1] [,2]
>>> [1,] 0.8727638 0.86572490
>>> [2,] 0.9293218 0.37718416
>>> [3,] 0.7123847 0.37813388
>>> [4,] 0.1626817 0.03974489
>>> [5,] 0.6394916 0.88299648
>>>
>> Hmisc already provides a function for doing this, rcorr(). Try to
>> compute correlations using Rcmdr for an example.
>>
>> Regards
>> Liviu
>>
>>
>>> (Take a look at the "Values" section in the help file for cor.test
>>> to get the names of other quantities of interest.)
>>>
>>> The main advantage to this approach is that if you add more matrices
>>> to the allmats list, the other steps automaticall take it into account.
>>>
>>> Hope this helps.
>>> - Phil Spector
>>> Statistical Computing Facility
>>> Department of Statistics
>>> UC Berkeley
>>> spec...@stat.berkeley.edu
>>>
>>>
>>>
>>>
>>>
>>> On Tue, 21 Dec 2010, govin...@msu.edu wrote:
>>>
>>>>
>>>>
>>>> Hi,
>>>>
>>>> I am having trouble with matrices. I?have 2 matrices as given below, and I
>>>> am interested in using these matrices inside "for" loops used to calculate
>>>> correlations. I am creating a list with the names of the matrices assuming
>>>> this list could be indexed inside the 'for' loop to retrieve the matrix
>>>> values. But, as expected the code throws out an error. Can someone
>>>> suggest a
>>>> better way to call these matrices inside the loops?
>>>>
>>>> ts.m.dmi <- matrix(c(1:20), 4, 5)
>>>> ts.m.soi <- matrix(c(21:40), 4, 5)
>>>> ts.m.pe <- matrix(c(21:40), 4, 5)
>>>>
>>>> factors <- c("ts.m.dmi", "ts.m.soi")
>>>> for (j in 0:1){
>>>> y <- factors[j+1]
>>>>
>>>> for (i in 1:5){
>>>>
>>>> cor.pe.y <- cor(ts.m.pe[,2], y[,i])
>>>> ct.tst <- cor.test(ts.m.pe[,2], y[,i])
>>>> }
>>>> }
>>>>
>>>> Thanks for your time.
>>>>
>>>> --
>>>> Regards,
>>>> Maha
>>>> Graduate Student
>>>> [[alternative HTML version deleted]]
>>>>
>>>>
>>>
>>> ______________________________________________
>>> R-help@r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>>
>>
>> --
>> Do you know how to read?
>> http://www.alienetworks.com/srtest.cfm
>> http://goodies.xfce.org/projects/applications/xfce4-dict#speed-reader
>> Do you know how to write?
>> http://garbl.home.comcast.net/~garbl/stylemanual/e.htm#e-mail
>>
> [[alternative HTML version deleted]]
>
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
--
Bert Gunter
Genentech Nonclinical Biostatistics
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