[R] multivariate version of aggregate

[Rui Barradas]

Hello,

You can solve your problem using only base R, with no need for an 
external package. The two instrucitons below are two ways of doing the same.



sapply(split(testframe, indices), function(x) cor(x[, 1], x[, 2]))

as.vector(by(testframe, indices, function(x) cor(x[, 1], x[, 2])))



Hope this helps,

Rui Barradas

Em 28-06-2013 09:31, Jannis escreveu:
> Yes, I had a look at that function. From the documentation, however, it
> did not get clear to me how to split the dataframe into subsets of rows
> based on an index argument. Like:
>
>
> testframe <- data.frame(a=rnorm(100), b = rnorm(100))
> indices      <- rep(c(1,2), each = 50)
>
>
> results <- ddply(.data = testframe, INDICES= indices, .fun = function(x)
> corr(x[,1], x[,2]))
>
> Where the last command would yield the correlations between column 1 and
> 2 of the first 50 and of the last 50 values.
>
> Any ideas?
>
> Jannis
>
> On 27.06.2013 21:43, Greg Snow wrote:
>> Look at the plyr package, probably the ddply function in that
>> package.  You
>> can write your own function to do whatever you want on the pieces of the
>> split apart object.  Correlation between a specified pair of columns
>> would
>> be simple.
>>
>>
>> On Thu, Jun 27, 2013 at 11:26 AM, Jannis <bt_jannis at yahoo.de> wrote:
>>
>>> Dear List members,
>>>
>>>
>>> i am seeking a multivariate version of aggregate. I want to compute, fro
>>> example the correlation between subsets of two vectors. In aggregate,
>>> i can
>>> only supply one vector with indices for subsets. Is  there ready
>>> function
>>> for this or do i need to program my own?
>>>
>>>
>>> Cheers
>>> Jannis
>>>
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>>
>>
>
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