Hi All,
I have couple of clarifications on R run-time performance. I have R-3.2.2
package compiled for MIPS64 and am running it on my linux machine with
mips64 processor (core speed 1.5GHz) and observing the following behaviors,
1. Applying "linear regression model" (lm) on 1MB of data (contains 1
column of 250K records) takes ~6 seconds to complete. Anyidea, is it an
expected behavior or not? If not, can you please the suggestions or options
to improve if we have any?
2. Also, the R process runtime virtual memory is increased by 40MB after
applying the linear model on 1MB data. Is it also expected behavior? If it
is expected, can you please share the insight of memory usage?
Thanks in advance.
Regards
Sasi
[[alternative HTML version deleted]]
______________________________________________
[email protected] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
