A mode of a sample is not ill-defined, it is just not unique.  Neither is a 
median, if you are interested in probability.

You can encapsulate mode, median and mean in a single formula.  Suppose y is a 
data vector and t is a scalar.  The a value of t which minimizes +/ (|y-t)^i 
[with special meaning for x^0: see below] is
- A mode of y if i=0.
-A median of y if i=1.
-The mean of y if i=2.
Here x^0 meas 1 if x=0 and 0 if x is nonzero.

John
________________________________
From: Programming <[email protected]> on behalf of Devon 
McCormick <[email protected]>
Sent: Friday, July 24, 2020 2:35 PM
To: J-programming forum <[email protected]>
Subject: [Jprogramming] Standard library version of statistical "mode"?

Hi - I've started reading "Fun Q" which is a book on machine learning using
the q language.  Early on, the author points out that his "mode" function -
where "mode" is stats-talk for "the most frequent observation" - is
order-dependent.

I checked my own "mode" and found that this is true of mine as well:
mode
   ~. {~ [: (i. >./) #/.~
   mode 1 2 2 3 3
2
   mode 1 3 3 2 2
3

This might be an ill-defined statistical concept but does anyone have any
insight based on practice?  Is this order-dependence just a weakness of the
definition of "mode"?

I could not find "mode" defined in any of the J standard libraries.

Thanks,

Devon

--

Devon McCormick, CFA

Quantitative Consultant
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