{"action":"created","issue":{"url":"https://api.github.com/repos/scipy/scipy/issues/6763","repository_url":"https://api.github.com/repos/scipy/scipy","labels_url":"https://api.github.com/repos/scipy/scipy/issues/6763/labels{/name}","comments_url":"https://api.github.com/repos/scipy/scipy/issues/6763/comments","events_url":"https://api.github.com/repos/scipy/scipy/issues/6763/events","html_url":"https://github.com/scipy/scipy/pull/6763","id":187523006,"number":6763,"title":"ENH: Weighted tau","user":{"login":"vigna","id":1464942,"avatar_url":"https://avatars.githubusercontent.com/u/1464942?v=3","gravatar_id":"","url":"https://api.github.com/users/vigna","html_url":"https://github.com/vigna","followers_url":"https://api.github.com/users/vigna/followers","following_url":"https://api.github.com/users/vigna/following{/other_user}","gists_url":"https://api.github.com/users/vigna/gists{/gist_id}","starred_url":"https://api.github.com/users/vigna/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/vigna/subscriptions","organizations_url":"https://api.github.com/users/vigna/orgs","repos_url":"https://api.github.com/users/vigna/repos","events_url":"https://api.github.com/users/vigna/events{/privacy}","received_events_url":"https://api.github.com/users/vigna/received_events","type":"User","site_admin":false},"labels":[{"id":37340735,"url":"https://api.github.com/repos/scipy/scipy/labels/enhancement","name":"enhancement","color":"bfe5bf","default":true},{"id":37340722,"url":"https://api.github.com/repos/scipy/scipy/labels/scipy.stats","name":"scipy.stats","color":"207de5","default":false}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":5,"created_at":"2016-11-05T21:03:41Z","updated_at":"2016-11-06T10:49:01Z","closed_at":null,"pull_request":{"url":"https://api.github.com/repos/scipy/scipy/pulls/6763","html_url":"https://github.com/scipy/scipy/pull/6763","diff_url":"https://github.com/scipy/scipy/pull/6763.diff","patch_url":"https://github.com/scipy/scipy/pull/6763.patch"},"body":"This pull request implements a weighted version of Kendall's 𝛕: in the weighted 𝛕, exchanges have different importance, and in general having important elements in the wrong order creates more discordance than having unimportant elements in the wrong order.\r\n\r\nDISCLAIMER: albeit definitions of weighted versions of Kendall's 𝛕 go back at least to Shieh's 1997 paper, the definition and algorithm implemented here appeared in a paper I wrote published at WWW 2015. The definition I give encompasses all previous attempts (so one can, say, use this code to compute Shieh's variant) and is meaningful also in the presence of ties.\r\n\r\nI was lecturing about the weighted 𝛕 at ISI in Turin recently and someone in the audience said \"oh that's so nice but we will use it only if it's in SciPy\". So here I am.\r\n\r\nI understand that it might not be considered a good idea to add to SciPy something so new (and possibly useless). But I think it's interesting, in particular for big data analysis. Our use case is comparing complex centralities with indegrees: there are tons of ties, and moreover you're not really interested in what happens in the large tail of very-low-indegree nodes—you want to know whether there is correlation on the important nodes.\r\n\r\nNote that the null distribution is not known, so there's no p-value: the code computes only the measure of correlation (the p-value is always NaN).\r\n\r\nThe code is by and large a rework of my code for #5754. Comments are more than welcome. Presently the I'm using fused types to generate 16 compiled variants handling 32/64-bits float/ints, but maybe we can reduce the choice to two types instead of four."},"comment":{"url":"https://api.github.com/repos/scipy/scipy/issues/comments/258673081","html_url":"https://github.com/scipy/scipy/pull/6763#issuecomment-258673081","issue_url":"https://api.github.com/repos/scipy/scipy/issues/6763","id":258673081,"user":{"login":"vigna","id":1464942,"avatar_url":"https://avatars.githubusercontent.com/u/1464942?v=3","gravatar_id":"","url":"https://api.github.com/users/vigna","html_url":"https://github.com/vigna","followers_url":"https://api.github.com/users/vigna/followers","following_url":"https://api.github.com/users/vigna/following{/other_user}","gists_url":"https://api.github.com/users/vigna/gists{/gist_id}","starred_url":"https://api.github.com/users/vigna/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/vigna/subscriptions","organizations_url":"https://api.github.com/users/vigna/orgs","repos_url":"https://api.github.com/users/vigna/repos","events_url":"https://api.github.com/users/vigna/events{/privacy}","received_events_url":"https://api.github.com/users/vigna/received_events","type":"User","site_admin":false},"created_at":"2016-11-06T10:49:01Z","updated_at":"2016-11-06T10:49:01Z","body":"Can anybody help with the following error?\r\n\r\n    ERROR: objects in scipy.stats.__all__ but not in refguide::\r\n\r\n        weightedtau\r\n\r\n    ERROR: refguide or doctests have errors\r\n\r\nI've trying to understand what's wrong, but I'm clueless."}}
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