Displaying 7 results from an estimated 7 matches for "shellsort".
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1997 Sep 03
1
R-alpha: speed of sort(.) and order(.)
sort() and order() are not quite the same, as "one knows":
o order allows breaking ties by more than one argument;
o sort allows a 'partial' and 'na.last' argument
Still, the following timing (on a `simple' UltraSparc I)
suggest that actually two different algorithms are used
> N <- 10000
> typeof(x0 <- 1:N) # --- x0 : already sorted ---
[1]
2006 Mar 11
1
Quicker quantiles?
Motivated by Deepayan's recent inquiries about the efficiency of the
R 'quantile'
function:
http://tolstoy.newcastle.edu.au/R/devel/05/11/3305.html
http://tolstoy.newcastle.edu.au/R/devel/06/03/4358.html
I decided to try to revive an old project to implement a version of
the Floyd
and Rivest (1975) algorithm for finding quantiles with O(n)
comparisons. I
used
2001 Apr 27
2
Benchmarking R, why sort() is so slow?
Hello everybody,
I am making a modified version of "Stephan Steinhaus' benchmark test for
number crunching, v. 2, (see
http://www.scinetificweb.com/ncrunch/ncrunch.pdf for the original version),
comparing several functions of some math/stat software. R is not performing
bad at all... except for the sorting of a 1,100,000 random vector (test #3)
which is the worst of all (see cell F3 in
2001 Apr 27
2
Benchmarking R, why sort() is so slow?
Hello everybody,
I am making a modified version of "Stephan Steinhaus' benchmark test for
number crunching, v. 2, (see
http://www.scinetificweb.com/ncrunch/ncrunch.pdf for the original version),
comparing several functions of some math/stat software. R is not performing
bad at all... except for the sorting of a 1,100,000 random vector (test #3)
which is the worst of all (see cell F3 in
2001 Feb 16
1
Sub_scribe and a question
...s not
representation of real problems, and for many such (and even for
rnorm(1e6)) one can do even better by e.g radix sorting. So if you know
something about the input you make your package look better. Again,
a problem with benchmarking.
>> Peter Dalgaard
> The internal algorithm is a shellsort, which is supposedly of
> complexity O(n^1.25) and has decent worst-case behaviour. Other
> algorithms like quicksort have typical performance of O(n log n) but
> extreme cases of O(n^2).
>
> For large vectors the O(n^.25/log(n)) relative complexity is going to
> make a difference...
2011 Apr 13
0
R 2.13.0 is released
...not preserved; this may be addressed in the future).
? options("install.lock") may be set to FALSE so that
install.packages() defaults to --no-lock installs, or (on
Windows) to TRUE so that binary installs implement locking.
? sort(partial = p) for large p now tries Shellsort if quicksort is
not appropriate and so works for non-numeric atomic vectors.
? sapply() gets a new option simplify = "array" which returns a
?higher rank? array instead of just a matrix when FUN() returns a
dim() length of two or more.
replicate() has this op...
2011 Apr 13
0
R 2.13.0 is released
...not preserved; this may be addressed in the future).
? options("install.lock") may be set to FALSE so that
install.packages() defaults to --no-lock installs, or (on
Windows) to TRUE so that binary installs implement locking.
? sort(partial = p) for large p now tries Shellsort if quicksort is
not appropriate and so works for non-numeric atomic vectors.
? sapply() gets a new option simplify = "array" which returns a
?higher rank? array instead of just a matrix when FUN() returns a
dim() length of two or more.
replicate() has this op...