sd()
will compute the standard deviations of the columns, equivalent
to calling apply(x, MARGIN=2, FUN=sd)
(which will work for
distributed matrices, by the way). However, this should be much faster and
use less memory than apply()
. If reduce=FALSE
then the return
is a distributed matrix consisting of one (global) row; otherwise, an
R
vector is returned, with ownership of this vector determined by
proc.dest
.
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x |
numeric distributed matrices. |
na.rm |
Logical; if TRUE, then |
reduce |
logical or string. See details |
proc.dest |
Destination process (or 'all') if a reduction occurs |
Returns a distributed matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 |
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