{"action":"created","issue":{"url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2925","repository_url":"https://api.github.com/repos/statsmodels/statsmodels","labels_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2925/labels{/name}","comments_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2925/comments","events_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2925/events","html_url":"https://github.com/statsmodels/statsmodels/pull/2925","id":153094332,"number":2925,"title":"WIP: Power transforms (specifically: Box-Cox) mixin","user":{"login":"N-Wouda","id":16272507,"avatar_url":"https://avatars.githubusercontent.com/u/16272507?v=3","gravatar_id":"","url":"https://api.github.com/users/N-Wouda","html_url":"https://github.com/N-Wouda","followers_url":"https://api.github.com/users/N-Wouda/followers","following_url":"https://api.github.com/users/N-Wouda/following{/other_user}","gists_url":"https://api.github.com/users/N-Wouda/gists{/gist_id}","starred_url":"https://api.github.com/users/N-Wouda/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/N-Wouda/subscriptions","organizations_url":"https://api.github.com/users/N-Wouda/orgs","repos_url":"https://api.github.com/users/N-Wouda/repos","events_url":"https://api.github.com/users/N-Wouda/events{/privacy}","received_events_url":"https://api.github.com/users/N-Wouda/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/statsmodels/statsmodels/labels/comp-base","name":"comp-base","color":"ededed"},{"url":"https://api.github.com/repos/statsmodels/statsmodels/labels/comp-tsa","name":"comp-tsa","color":"ededed"},{"url":"https://api.github.com/repos/statsmodels/statsmodels/labels/type-enh","name":"type-enh","color":"99ffff"}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":26,"created_at":"2016-05-04T19:24:48Z","updated_at":"2016-07-07T08:01:47Z","closed_at":null,"pull_request":{"url":"https://api.github.com/repos/statsmodels/statsmodels/pulls/2925","html_url":"https://github.com/statsmodels/statsmodels/pull/2925","diff_url":"https://github.com/statsmodels/statsmodels/pull/2925.diff","patch_url":"https://github.com/statsmodels/statsmodels/pull/2925.patch"},"body":"As per #1309, this is an early PR to provide power transformations for data series. For now this is limited to Box-Cox transformations, but if I find the time I'd like to include more.\r\n\r\n@josef-pkt I'm not that sure on where this file should be located. I felt `/tools/transform.py` was a proper location, but if you have any suggestions that'd be great."},"comment":{"url":"https://api.github.com/repos/statsmodels/statsmodels/issues/comments/231009916","html_url":"https://github.com/statsmodels/statsmodels/pull/2925#issuecomment-231009916","issue_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2925","id":231009916,"user":{"login":"N-Wouda","id":16272507,"avatar_url":"https://avatars.githubusercontent.com/u/16272507?v=3","gravatar_id":"","url":"https://api.github.com/users/N-Wouda","html_url":"https://github.com/N-Wouda","followers_url":"https://api.github.com/users/N-Wouda/followers","following_url":"https://api.github.com/users/N-Wouda/following{/other_user}","gists_url":"https://api.github.com/users/N-Wouda/gists{/gist_id}","starred_url":"https://api.github.com/users/N-Wouda/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/N-Wouda/subscriptions","organizations_url":"https://api.github.com/users/N-Wouda/orgs","repos_url":"https://api.github.com/users/N-Wouda/repos","events_url":"https://api.github.com/users/N-Wouda/events{/privacy}","received_events_url":"https://api.github.com/users/N-Wouda/received_events","type":"User","site_admin":false},"created_at":"2016-07-07T08:01:47Z","updated_at":"2016-07-07T08:01:47Z","body":"> However, if there are explanatory variables, like in ARMAX or OLS, then fluctuations in endog will come to a large extend from fluctuations in exog, and the variance of raw endog will or can be much larger than the residual variance and does not need to have a uniform pattern if exogs have different smoothness across time.\r\n\r\nI must honestly admit I have not yet looked into the application of these methods to specific models. I assumed R had done so already, and I can look there for some inspiration. "}}
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