| To: | courses@zanybooks.com |
|---|---|
| Subject: | Re: Internal rounding errors |
| From: | Thomas Lumley <tlumley@u.washington.edu> |
| Date: | Tue, 3 Mar 2009 07:45:37 -0800 (PST) |
| Cc: | s-news@lists.biostat.wustl.edu |
| In-reply-to: | <20090303083828.b21645f2bceb2bcc4cba8e709837b1d9.8d29d45cf1.wbe@email.secureserver.net> |
On Tue, 3 Mar 2009 courses@zanybooks.com wrote: Using R (not S-Plus) yields the following: > data3=1:25+rnorm(25) > temp=data3-mean(data3) > sum(temp) [1] 1.154632e-14 And so? sum(1:25)*.Machine$double.eps
[1] 7.21645e-14
so the rounding error is about six times smaller than a bound based on machine
precision, and is very close to mean(1:25)*sqrt(25)*.Machine$double.eps, which
seems a reasonable expected value for the internal rounding error.
You weren't expecting zero, were you?
-thomas
Thomas Lumley Assoc. Professor, Biostatistics
tlumley@u.washington.edu University of Washington, Seattle
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