Thanks for the suggestion.
I found some documentation on why accessing a data.gram using the
matrix notation (e.g., [i,j]) is so expensive, which was the cause of
the problem.
regards,
Roberto
On Thu, Oct 22, 2009 at 12:05 AM, Jim Holtman jholt...@gmail.com wrote:
try running Rprof on the
Hi everybody,
I noticed a strange behavior when using loops versus apply() on a data frame.
The example below explicitly computes a distance matrix given a
dataset. When the dataset is a matrix, everything works fine. But when
the dataset is a data.frame, the dist.for function written using
try running Rprof on the two examples to see what the difference is.
what you will probably see is a lot of the time on the dataframe is
spent in accessing it like a matrix ('['). Rprof is very helpful to
see where time is spent in your scripts.
Sent from my iPhone
On Oct 21, 2009, at
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