what does cut(data, breaks=n) actually do?

Hello,

I'm trying to bin a quantity into 2-3 bins for calculating entropy and
mutual information.  One of the approaches I'm exploring is the cut()
function, which is what the mutualInfo function in binDist uses.  When it's
called in the format cut(data, breaks=n), it somehow splits the data into n
distinct bins.  Can anyone tell me how cut() decides where to cut?

  

This is one case where reading the actual R code is easier that 
explaining what it does.  From cut.default

    if (length(breaks) == 1) {
        if (is.na(breaks) | breaks < 2)
            stop("invalid number of intervals")
        nb <- as.integer(breaks + 1)
        dx <- diff(rx <- range(x, na.rm = TRUE))
        if (dx == 0)
            dx <- rx[1]
        breaks <- seq.int(rx[1] - dx/1000, rx[2] + dx/1000, length.out = nb)
    }

so basically it takes the range, extends it a bit and splits in into 
<breaks> equally long segments.

(For the sometimes more attractive option of splitting into groups of 
roughly equal size, there is cut2 in the Hmisc package, or use quantile())

O__  ---- Peter Dalgaard             ?ster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
 (*) \(*) -- University of Copenhagen   Denmark          Ph:  (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)                  FAX: (+45) 35327907

cut(data, breaks=n)
splits the data in n bins of (approximately) the same size.

The used size is obtained by:
max(data) - min(data)
------------------------------------
                 n

 > x=rnorm(x)
 > cut(x,breaks=3)
 [1] (1.79,9.97]  (-6.39,1.79] (9.97,18.2]  (9.97,18.2]  (-6.39,1.79]
 [6] (1.79,9.97]  (-6.39,1.79] (1.79,9.97]  (-6.39,1.79] (-6.39,1.79]
Levels: (-6.39,1.79] (1.79,9.97] (9.97,18.2]

Then you have:
 > 18.2-9.97
[1] 8.23
 > 9.97-1.79
[1] 8.18
 > 1.79+6.39
[1] 8.18
 >

 > (max(x)-min(x))/3
[1] 8.164187

I don't know the reasons for the little differences (I am wondering about).
I hope it is useful.
domenico

Hello,

I'm trying to bin a quantity into 2-3 bins for calculating entropy and
mutual information.  One of the approaches I'm exploring is the cut()
function, which is what the mutualInfo function in binDist uses.  When it's
called in the format cut(data, breaks=n), it somehow splits the data into n
distinct bins.  Can anyone tell me how cut() decides where to cut?

Thanks,

Melissa



---------------------------------------------------------------
Melissa Cline, Independent Investigator
MCD Biology, UCSC

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