[R] [Fwd: Excluding data with apply]

[Dimitris Rizopoulos]

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

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