On 1/23/2012 8:40 PM, David Winsemius wrote:
On Jan 23, 2012, at 2:30 PM, Petr Savicky wrote:
On Mon, Jan 23, 2012 at 01:08:03PM -0500, R. Michael Weylandt wrote:
I'd do something like
apply(subER, 1, function(x) which(x %in% sort(x)[1:4]))
E.g.
subER <- matrix(sample(100), 10)
Hi.
This is OK, if there are four smallest values, which
are different from the rest. For the first row in
subER <- rbind(c(1, 2, 2, 3, 3, 3, 5, 6), 8:1)
the function determines the bound 3 and returns the
indices of the 6 positions with 1, 2, 3 from the first
row. So, the result is not a matrix, but a list.
apply(subER, 1, function(x) which(x %in% sort(x)[1:4]))
[[1]]
[1] 1 2 3 4 5 6
[[2]]
[1] 5 6 7 8
The following solves ties by choosing the smaller index.
apply(subER, 1, function(x) order(x)[1:4])
[,1] [,2]
[1,] 1 8
[2,] 2 7
[3,] 3 6
[4,] 4 5
If the indices should be ordered, then try the following
apply(subER, 1, function(x) sort(order(x)[1:4]))
[,1] [,2]
[1,] 1 5
[2,] 2 6
[3,] 3 7
[4,] 4 8
And if only the lowest four instances were desired (in ascending order)
then this would work (and I transposed to bring back to the original
structure):
t(apply(subER, 1, function(x) x[order(x)][1:4]))
[,1] [,2] [,3] [,4]
[1,] 1 2 2 3
[2,] 1 2 3 4
Yet another solution is:
subER <- matrix(sample(100), 10)
matrix(subER[order(row(subER), subER)],
ncol = ncol(subER), byrow = TRUE)[, 1:4]
Cheers,
Dimitris
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
Web: http://www.erasmusmc.nl/biostatistiek/
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