You are trying to test the equality of a matrix to a scalar, which
will produce a logical vector. You are also using && in an apparent
attempt to conjoin a complex object which will probably not give you
the results you expect in that context either since it would only
return a single TRUE or FALSE. Use & in situations where you want
element-wise comparisons of vectors.
You might start by experimenting on a much smaller object and seeing
how your efforts at indexing could be improved.
> X <- matrix(c(runif(9)),nrow=3)
> X
[,1] [,2] [,3]
[1,] 0.4151688 0.2116687 0.6049845
[2,] 0.7924464 0.6624862 0.8444203
[3,] 0.2634175 0.3357537 0.6923846
> X>.8
[,1] [,2] [,3]
[1,] FALSE FALSE FALSE
[2,] FALSE FALSE TRUE
[3,] FALSE FALSE FALSE
#Use apply to create a logical vector that flags the unwanted rows:
> apply(X,1,function(x) max(x) > 0.8)
[1] FALSE TRUE FALSE
#Now use that construction on both rows and colums
> X[-apply(X,1,function(x) max(x) > 0.8), -apply(X,2,function(x)
max(x) > 0.8)]
[,1] [,2]
[1,] 0.6624862 0.8444203
[2,] 0.3357537 0.6923846
--
David
On May 8, 2009, at 1:39 AM, onyourmark wrote:
Hi. I have a correlation matrix 'x' which is of size 923x923
I need to remove variables that are highly correlated. I don't have a
sophisticated way of selecting which of the two in a highly
correlated pair
to remove. I thought I would just go through each entry of the
correlation
matrix and if it is greater than 0.6 (or less than -0.6) I will
remove that
column and then redo the check from scratch with the matrix (where
now the
matrix has one less column).
As a test, I tried if ((x >.2 || x<(-.2)) && col(x)!=row(x)) {x=x[,-
col(x)]}
but it does not remove any columns.
Also, I realized that I actually need to pull out the row that is
associated
with that variable as well, and so perhaps the section inside {}
needs to be
something like:
{x=x[-col(x),-col(x)]
Any idea on how to do this?
Thank you.
--
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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