On Feb 22, 2012, at 4:01 PM, Ben quant wrote:
Hello,
What is the best way to get ranks for a vector of values, limit the
range
of rank values and create equal count in each group? I call this
uniform
ranking...uniform count/number in each group.
Here is an example using three groups:
Say I have values:
x = c(3, 2, -3, 1, 0, 5, 10, 30, -1, 4)
names(x) = letters[1:10]
x
a b c d e f g h i j
3 2 -3 1 0 5 10 30 -1 4
I would like:
a b c d e f g h i j
2 2 1 2 1 3 3 3 1 3
Same thing as above, maybe easier to see:
c i e d b a j f g h
-3 -1 0 1 2 3 4 5 10 30
I would get:
c i e d b a j f g h
1 1 1 2 2 2 3 3 3 3
Note that there are 4 values with a rank of 3 because I can't get even
numbers (10/3 = 3.333).
Been to ?sort, ?order, ?quantile, ?cut, and ?split.
You may need to look more carefully at the definitions and adjustments
to `cut` and `quantile` but this does roughly what you asked:
n=3
as.numeric( cut(x, breaks=quantile(x, prob=(0:n)/n) ,
include.lowest=TRUE) )
@ [1] 1 1 1 1 2 2 2 3 3 3
It a fairly common task and Harrell's cut2 function has a g= parameter
(for number of groups) that I generally use:
library(Hmisc)
> cut2(x, g=3)
[1] [-3, 2) [-3, 2) [-3, 2) [-3, 2) [ 2, 5) [ 2, 5) [ 2, 5) [ 5,30]
[ 5,30] [ 5,30]
Levels: [-3, 2) [ 2, 5) [ 5,30]
> as.numeric( cut2(x, g=3))
[1] 1 1 1 1 2 2 2 3 3 3
Thanks,
Ben
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