Computing the mode

     The problem is that 'the statistic "mode" of a sample' has 
no 
clear definition.  If the distribution is highly discrete, then 
the 
following will do the job: 

set.seed(1)
X <- rpois(11,1)
(nX <- table(X))

X
0 1 2 3
4 4 2 1

names(nX)[nX==max(nX)]

[1] "0" "1"

     However, if the data are continuous with no 2 numbers 
exactly 
equal, then the "mode" depends on the procedure, e.g., the 
specific 
selection of breakpoints for a histogram.  If you insist on 
finding 
something, you can try "www.r-project.org" -> search -> "R site 
search" 
for something like ""nonparametric density estimation" and / or 
"kernel 
density estimator". 

     hope this helps. 
     spencer graves
     p.s.  This has been discussed recently on this list, but I 
could 
not easily find it in the archives. 

Aurora Torrente wrote:

Hi all,
I think this question could be quite trivial, but I can?t find 

out the 

solution... How can you compute the statistic "mode" of a 

sample, in 

case it exists (as mode() returns the mode of an object)? I 

tried 

help.search("mode") but I couldn't find a clue...
Any help would be much appreciated. Regards,

       Aurora