Thank you, Rui! This is incredibly helpful -- anonymous functions
are new to me, and I appreciate being shown how useful they are.
Best regards,
David
On Wed, Dec 12, 2012 at 10:12 AM, Rui Barradas wrote:
> Hello,
>
> As for the first question try
>
> scoreset <- lapply(pcl, function(x) x$scor
Hello,
As for the first question try
scoreset <- lapply(pcl, function(x) x$scores[, 1])
do.call(cbind, scoreset)
As for the second question, you want to know which columns in 'datasets'
have NA's?
colidx <- apply(datasets, 2, function(x) any(is.na(x)))
datasets[, colidx] # These have NA's
Sorry, I just realized I didn't send the message below in plain text.
-David Romano
On Wed, Dec 12, 2012 at 9:14 AM, David Romano wrote:
>
> Hi everyone,
>
> Suppose I have a 3D array of datasets, where say dimension 1 corresponds
> to cases, dimension 2 to datasets, and dimension 3 to observatio
Hi everyone,
Suppose I have a 3D array of datasets, where say dimension 1 corresponds to
cases, dimension 2 to datasets, and dimension 3 to observations within a
dataset. As an example, suppose I do the following:
> x <- sample(1:20, 48, replace=TRUE)
> datasets <- array(x, dim=c(4,3,2))
Here,
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