Dear developers,
since running 'example(hist)' produces
...
hist> sum(r$density * diff(r$breaks)) # == 1
[1] 0.9999999
...
I suppose that the current behaviour of hist() is not as intended (and
documented).
So, please find attached (and inline below) a (trivial) patch for
hist.default().
Best wishes
Martin
Index: src/library/graphics/R/hist.R
==================================================================---
src/library/graphics/R/hist.R (revision 51652)
+++ src/library/graphics/R/hist.R (working copy)
@@ -111,7 +111,7 @@
stop("negative 'counts'. Internal Error in C-code for
\"bincount\"")
if (sum(counts) < n)
stop("some 'x' not counted; maybe 'breaks' do not span
range of 'x'")
- dens <- counts/(n*h)
+ dens <- counts/(n*diff(breaks))
mids <- 0.5 * (breaks[-1L] + breaks[-nB])
r <- structure(list(breaks = breaks, counts = counts,
intensities = dens,
Martin Becker wrote:> Dear developers,
>
> the current implementation of hist.default() calculates 'density'
(and
> 'intensities') as
> dens <- counts/(n*h)
> where h has been calculated before as
> h <- diff(fuzzybreaks)
> which results in 'fuzzy' values for the density, see e.g.
>
> > tmp <- hist(1:10,breaks=c(-2.5,2.5,7.5,12.5),plot=FALSE)
> > print(tmp$density,digits=15)
> [1] 0.0399999920000016 0.1000000000000000 0.0600000000000000
>
> Since hist.default()$breaks are not the fuzzy breaks used for the
> calculation of dens, the sum of the bins' area is significantly
> different from 1 in many cases, see e.g.
>
> > print(sum(tmp$density*diff(tmp$breaks)),digits=15)
> [1] 0.999999960000008
>
> Is this intended, or should the calculation of dens read
> dens <- counts/(n*diff(breaks))
> instead (or should hist.default()$breaks return the fuzzy breaks)?
>
> Best wishes
> Martin
>
>
--
Dr. Martin Becker
Statistics and Econometrics
Saarland University
Campus C3 1, Room 217
66123 Saarbruecken
Germany
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