[Moved to R-devel, as more appropriate.]
On Mon, 5 Mar 2001, Jari Oksanen wrote:
> Canberra distance is defined in function `dist' (standard library
`mva') as
>
> sum(|x_i - y_i| / |x_i + y_i|)
>
> Obviously this is undefined for cases where both x_i and y_i are zeros.
Since
> double zeros are common in many data sets, this is a nuisance. In our
field
> (from which the distance is coming), it is customary to remove double
zeros:
> contribution to distance is zero when both x_i and y_i are zero. Could it
be
> possible to have this kind of feature in R as well?
>
> It seems that this would do the trick without breaking applications where
> double zeros do not occur:
I am sure we should do something, but is this exactly right? From dist()
in the R-devel version (1.3.x, eventually) I have enabled the handling of
missing values. With this solution, identically zero elements contribute
zero to the distance, and are not regarded as missing. Canberra is
similar to binary, where x_i = y_i = 0 is treated as equivalent to
missing. The issue is if count should be incremented if
sum == 0.0 or not.
A related issue is the test (sum > 0.0). I guess there are potential
problems with optimization on machines that use extended-precision
arithmetic, where sum might be non-zero in a register but zero if stored.
Not sure if that can actually happen, but a tolerance (e.g. machar's
xmax) is usually safer.
>
> --- R-1.2.2/src/appl/distance.c Sun Oct 15 18:13:25 2000
> +++ R-work/src/appl/distance.c Mon Mar 5 10:16:53 2001
> @@ -93,5 +93,5 @@
> double R_canberra(double *x, int nr, int nc, int i1, int i2)
> {
> - double dist;
> + double dist, sum;
> int count, j;
>
> @@ -100,5 +100,7 @@
> for(j=0 ; j<nc ; j++) {
> if(R_FINITE(x[i1]) && R_FINITE(x[i2])) {
> - dist += fabs(x[i1] - x[i2])/fabs(x[i1] + x[i2]);
> + sum = fabs(x[i1] + x[i2]);
> + if (sum > 0.0)
> + dist += fabs(x[i1] - x[i2])/sum;
> count++;
> }
>
>
>
> Best wishes, Jari Oksanen
> --
> Jari Oksanen -- Dept Biology, Univ Oulu, 90014 Oulu, Finland
> Ph. +358 8 5531526 (job), mobile +358 40 5136529
> email jari.oksanen@oulu.fi, homepage http://cc.oulu.fi/~jarioksa/
>
>
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--
Brian D. Ripley, ripley@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272860 (secr)
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