Indeed, 4) would definitely make sense.
Rankings are typically constructed based on some sort of statistical
measure.

Cyril Briquet
>Phil Steitz a écrit :
>> MATH136 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 hardcode 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 ?
> Luc
>> Phil
