{"action":"created","comment":{"url":"https://api.github.com/repos/statsmodels/statsmodels/pulls/comments/216176836","pull_request_review_id":153600083,"id":216176836,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIxNjE3NjgzNg==","diff_hunk":"@@ -0,0 +1,140 @@\n+.. module:: statsmodels.base.optimizer\n+.. currentmodule:: statsmodels.base.optimizer\n+\n+Optimization\n+============\n+","path":"docs/source/optimization.rst","position":6,"original_position":6,"commit_id":"b694f05e8d195e8a87a635e16719942bb8fea5de","original_commit_id":"71587ae4a730fe793c6040eee0b23820c16d5baf","user":{"login":"josef-pkt","id":440735,"node_id":"MDQ6VXNlcjQ0MDczNQ==","avatar_url":"https://avatars1.githubusercontent.com/u/440735?v=4","gravatar_id":"","url":"https://api.github.com/users/josef-pkt","html_url":"https://github.com/josef-pkt","followers_url":"https://api.github.com/users/josef-pkt/followers","following_url":"https://api.github.com/users/josef-pkt/following{/other_user}","gists_url":"https://api.github.com/users/josef-pkt/gists{/gist_id}","starred_url":"https://api.github.com/users/josef-pkt/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/josef-pkt/subscriptions","organizations_url":"https://api.github.com/users/josef-pkt/orgs","repos_url":"https://api.github.com/users/josef-pkt/repos","events_url":"https://api.github.com/users/josef-pkt/events{/privacy}","received_events_url":"https://api.github.com/users/josef-pkt/received_events","type":"User","site_admin":false},"body":"I just want us to mention the type of optimization methods without providing a full list of models.\r\n\r\n(actually it's not that difficult, skipping some models in the sandbox\r\nlinear regression OLS/WLS/GLS and VAR and VECM have closed for linalg estimators, \r\nonly RLM and GLM have IRLS, \r\nall others have only scipy optimizers + our newton.\r\nGLM is currently the only one with irls and scipy optimizers.\r\n\r\nThere are some hybrid versions like GLSAR that we don't mention.\r\n\r\n... maybe there would be more in a full list, e.g. fit_regularized in OLS/WLS and in GLM uses coordinate descend. \r\n)","created_at":"2018-09-10T00:30:03Z","updated_at":"2018-09-10T00:30:03Z","html_url":"https://github.com/statsmodels/statsmodels/pull/5097#discussion_r216176836","pull_request_url":"https://api.github.com/repos/statsmodels/statsmodels/pulls/5097","author_association":"MEMBER","_links":{"self":{"href":"https://api.github.com/repos/statsmodels/statsmodels/pulls/comments/216176836"},"html":{"href":"https://github.com/statsmodels/statsmodels/pull/5097#discussion_r216176836"},"pull_request":{"href":"https://api.github.com/repos/statsmodels/statsmodels/pulls/5097"}},"in_reply_to_id":216144626},"pull_request":{"url":"https://api.github.com/repos/statsmodels/statsmodels/pulls/5097","id":212823257,"node_id":"MDExOlB1bGxSZXF1ZXN0MjEyODIzMjU3","html_url":"https://github.com/statsmodels/statsmodels/pull/5097","diff_url":"https://github.com/statsmodels/statsmodels/pull/5097.diff","patch_url":"https://github.com/statsmodels/statsmodels/pull/5097.patch","issue_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/5097","number":5097,"state":"open","locked":false,"title":"DOC: Doc clean-up and additions","user":{"login":"thequackdaddy","id":8186432,"node_id":"MDQ6VXNlcjgxODY0MzI=","avatar_url":"https://avatars2.githubusercontent.com/u/8186432?v=4","gravatar_id":"","url":"https://api.github.com/users/thequackdaddy","html_url":"https://github.com/thequackdaddy","followers_url":"https://api.github.com/users/thequackdaddy/followers","following_url":"https://api.github.com/users/thequackdaddy/following{/other_user}","gists_url":"https://api.github.com/users/thequackdaddy/gists{/gist_id}","starred_url":"https://api.github.com/users/thequackdaddy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/thequackdaddy/subscriptions","organizations_url":"https://api.github.com/users/thequackdaddy/orgs","repos_url":"https://api.github.com/users/thequackdaddy/repos","events_url":"https://api.github.com/users/thequackdaddy/events{/privacy}","received_events_url":"https://api.github.com/users/thequackdaddy/received_events","type":"User","site_admin":false},"body":"It feels like I'm on a doc binge. But writing docs is often a good way to better understand the tool you are using. \r\n\r\nAfter playing with the website for a bit, I thought to myself that it would be nice if we could clean-up some of the docs. There's some neat features of stats models that I think the docs could advertise more. I cleaned up the docs and removed some complicated instructions for things that are out of date (I doubt any 32 bit windows user is developing, they'll just install from conda or pip wheels) so I removed some things that are old. \r\n\r\nI'm happy to take a stab at adding some other docs--even if just a stub for now--if it can encourage us to organize some of this better. Things like robust covariance are neat and the fact that stats models make it so easy should be a relatively big selling point. Alas, we don't have docs/examples that really show it off, so at least starting it might be a good idea. If there are others, let me know. 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