Equal frequency discretization in R

Question

I\'m having trouble finding a function in R that performs equal-frequency discretization. I stumbled on the \'infotheo\' package, but after some testing I found that the al

Answer 1

EDIT : given your real goal, why don't you just do (corrected) :

 EqualFreq2 <- function(x,n){
    nx <- length(x)
    nrepl <- floor(nx/n)
    nplus <- sample(1:n,nx - nrepl*n)
    nrep <- rep(nrepl,n)
    nrep[nplus] <- nrepl+1
    x[order(x)] <- rep(seq.int(n),nrep)
    x
}

This returns a vector with indicators for which bin they are. But as some values might be present in both bins, you can't possibly define the bin limits. But you can do :

x <- rpois(50,5)
y <- EqualFreq2(x,15)
table(y)
split(x,y)

---

Original answer:

You can easily just use cut() for this :

EqualFreq <-function(x,n,include.lowest=TRUE,...){
    nx <- length(x)    
    id <- round(c(1,(1:(n-1))*(nx/n),nx))

    breaks <- sort(x)[id]
    if( sum(duplicated(breaks))>0 stop("n is too large.")

    cut(x,breaks,include.lowest=include.lowest,...)

}

Which gives :

set.seed(12345)
x <- rnorm(50)
table(EqualFreq(x,5))

 [-2.38,-0.886] (-0.886,-0.116]  (-0.116,0.586]   (0.586,0.937]     (0.937,2.2] 
             10              10              10              10              10 

x <- rpois(50,5)
table(EqualFreq(x,5))

 [1,3]  (3,5]  (5,6]  (6,7] (7,11] 
    10     13     11      6     10 

As you see, for discrete data an optimal equal binning is rather impossible in most cases, but this method gives you the best possible binning available.