The mode is a well defined concept for theoretical distributions, but much less 
well defined when applied to data.  Some attempts at getting the mode of data 
actually returns a quirk of rounding rather than anything informative about the 
data and the distribution that it represents.  This is especially true when the 
data is supposed to represent and underlying continuous distribution.  If the 
theorized distribution is discrete (Poisson, binomial, etc.) then the mode may 
be more meaningful (but can still be the result of a quirk of rounding).  For 
discrete distributions you can just use the table function to get all the 
counts and look for the largest (and look for other similar values to see if 
your single "mode" is really meaningful).  For continuous distributions you 
need to decide what you really want and what level of approximation you are 
willing to live with and what assumptions you are willing to make (one simple 
approach is just look at the histogram, if there is a c!
 lear peak, then that gives you a modal range).


-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.s...@imail.org
801.408.8111


> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> project.org] On Behalf Of djack...@miners.utep.edu
> Sent: Wednesday, April 14, 2010 8:55 PM
> To: r-help@r-project.org
> Subject: [R] Question about R mode
> 
> 
> Hello all,
> 
> I am using R to perform certain calculations on huge amounts of data.
> In short I need a function that does the mode function, ie returns the
> most common element.  I looked at the mode function in R but it seems
> to return the type of the data element you give it.  Does such a method
> exist?  I have tried googling this to no avail as all the results lead
> me back to the mode function I do not want.
> 
> Thanks,
> 
> Don
> 
>       [[alternative HTML version deleted]]
> 
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