Luc Maisonobe wrote:
Phil Steitz a écrit :
MATH-136 introduces rank correlation, with pluggable ranking algorithm.
The RankingAlgorithm interface and associated implementations are likely
to be reused elsewhere in the stat package. The question is where to
put RankingAlgorithm and its implementations. I would appreciate
feedback on the following alternatives.
0) Hold off introducing the algorithms at all - just hard-code the
conventional (ties get the average) algorithm into the Spearman's
correlation class to be included in the correlation package. See
comments in the JIRA issue.
1) Put RankingAlgorithm and its implementations into the correlation
package, where it will be first used.
2) Put them in util
3) Put them in stat.descriptive.rank
4) new package stat.ranking
I think 2) is the best, but appreciate feedback.
I would have chosen 4, but my lack of understanding about anything stat
related implies my opinion should not count here. The rationale is
probably where users without a priori knowledge of the library layout
would first search for such features. Are ranking algorithms used
outside of stat ?
None that we currently have, though rank transformation is a pretty
basic utility. Within stat, there are lots of non-parametric techniques
(such as Spearman's rank correlation) that apply rank transformations.
FWIW, R puts their version of this in the "base" package, which is sort
of like util for us. I am fine with 4) and would even be OK with 0),
since the current case does not really require it (i.e., I don't know
how meaningful the statistic is if you don't use ties-averaged as the
ranking algorithm). It will be useful, however, when we implement other
nonparametric stats to have these algorithms available.
Phil
Phil
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