I've fixed this by adding 0.5/mn to q. The problem (at least in principle)
with multiplying them all up is integer overflow.
By the time 0.5/mn underflows to zero, missing one value in the distribution
won't matter.
-thomas
On Fri, 18 Dec 2009, David John Allwright wrote:
Dear
I've fixed this by adding 0.5/mn to q. The problem (at least in principle)
with multiplying them all up is integer overflow.
By the time 0.5/mn underflows to zero, missing one value in the distribution
won't matter.
-thomas
On Fri, 18 Dec 2009, David John Allwright wrote:
Dear
On Fri, 18 Dec 2009, Gabriel Becker wrote:
My understanding is that all the really fast vectorized operations are
implemented down in C code, not in R. Thus if you wanted to write a
vectorized switch, which I agree would be rather nice to have, you'd need to
do it down there and then write a
On Tue, 15 Dec 2009, allwr...@maths.ox.ac.uk wrote; (in part)
x-1:5
y-c(2.5,4.5)
ks.test(x,y)
The value of the D_2,5 statistic is calculated as 0.4 correctly, but the
p-value is stated by R as 1, though in fact it should be 20/21=0.9524
What we seem to have here is a rounding error
On Tue, 15 Dec 2009, allwr...@maths.ox.ac.uk wrote; (in part)
x-1:5
y-c(2.5,4.5)
ks.test(x,y)
The value of the D_2,5 statistic is calculated as 0.4 correctly, but the
p-value is stated by R as 1, though in fact it should be 20/21=0.9524
What we seem to have here is a rounding error
m-matrix(c(0,1),ncol=2)
printCoefmat(m)
[,1] [,2]
[1,] NaN1
Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
3: In log(c(Inf, -Inf), 10) : NaNs produced
sessionInfo()
R version 2.9.0 beta
The explanation is that quote() is a primitive function and that the argument
matching rules do not apply to primitives. That section of the R Language
definition should say that primitives are excluded; it is documented in
?.Primitive.
-thomas
On Thu, 2 Apr 2009 w...@idi.ntnu.no
1. This is not a bug (as you seem to realize), so it should not be sent to
r-bugs.
2. You seem to want the drop=FALSE argument to [], as in FAQ 7.5
-thomas
On Wed, 13 Aug 2008 [EMAIL PROTECTED] wrote:
Good Day,
I can understand that after indexing a single column in a matrix, R
On Mon, 15 May 2006, [EMAIL PROTECTED] wrote:
Dear R developers,
We have a big SGI Origin computation server with 32 cpu's and 64 Gb of
RAM. In R 2.0.0 we could run large jobs, allocating 8 Gb of RAM was not
a problem, for example by running:
v1 - seq(1,2^29)
v2 - seq(1,2^29)
v3 -
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