you can use something like the following:
# your matrix
mat <- matrix(rnorm(20), 5, 4)
# an indicator matrix specifying which columns
# you want to exclude each time
ind <- matrix(sample(1:3, 18, TRUE), ncol = 3)
apply(ind, 1, function (i) mean(mat[, -i]))
where you may change mean() with whatever function or calculation you're
interested in.
I hope it helps.
Best,
Dimitris
Christian Kamenik wrote:> Dear all,
>
> I've got many responses to my initial question, which is stated below.
> However, from those responses it has become clear that I need to
> rephrase my problem. All responses dealt with subscripting the data
> matrix before 'apply' is run on it. But this is not want I wanted
to do.
> 'apply' cycles through rows or columns of a matrix, and runs a
function
> on each row or column individually. Now, instead of focusing on each
> individual row or column, I want to get rid of these rows or columns,
> and run the function on the remaining matrix.
> I could do this with a for loop, such as:
>
> x<-matrix(rnorm(100),20,5)
> for (i in 1:ncol(x)) print(mean(x[,-i]))
>
> But for more complex problems this becomes tedious...
>
> Any ideas would be highly appreciated, Christian
>
>>
>> Dear all,
>>
>> 'Apply' is a great thing for running functions on rows or
columns of a
>> matrix:
>>
>> X <- rnorm(20, mean = 0, sd = 1)
>> dim(X) <- c(5,4)
>> apply(X,2,sum)
>>
>> Is there a way to use apply for excluding rows or columns from a
>> matrix to run functions on the remaining rows or columns? I know, I
>> could do this with a 'for' loop, but 'apply' would be
much easier and
>> quicker, and require less programming...
>>
>> Cheers, Christian
>>
>
>
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014