R-beta: Quantile function

[Peter Dalgaard BSA]

Philippe Lambert <phlamber at luc.ac.be> writes:

> 
> Is the following behaviour of the quantile function what one would expect?
> > a <- 1:100
> > quantile(a,.6)
>  60% 
> 60.4 

Yes...

And so is
> quantile(1:10)
   0%   25%   50%   75%  100% 
 1.00  3.25  5.50  7.75 10.00 

(Note that *three* values, 8,9,10 fall above the 75% quantile!)

There are many possible definition of quantiles. R's (and Splus's) is
to put 0% at the minimum and 100% at the maximum, and in general, the
k-th smallest is at (k-1)/(n-1), with linear interpolation between the
points. (Try plot(quantile(rnorm(5),seq(0,1,.01))) to see it). 

This can surely be criticized, e.g. you'll always have 1 observation
below the 0.00..001 quantile! Alternatives might for example use
(k-.5)/n which puts the smallest observation at 1/2n, but then it's
tricky to define quantiles outside (1/2n,1-1/2n).


-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907

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