{"action":"created","issue":{"url":"https://api.github.com/repos/paul-buerkner/brms/issues/110","repository_url":"https://api.github.com/repos/paul-buerkner/brms","labels_url":"https://api.github.com/repos/paul-buerkner/brms/issues/110/labels{/name}","comments_url":"https://api.github.com/repos/paul-buerkner/brms/issues/110/comments","events_url":"https://api.github.com/repos/paul-buerkner/brms/issues/110/events","html_url":"https://github.com/paul-buerkner/brms/issues/110","id":173557917,"number":110,"title":"Implement additional response distributions","user":{"login":"paul-buerkner","id":12938496,"avatar_url":"https://avatars.githubusercontent.com/u/12938496?v=3","gravatar_id":"","url":"https://api.github.com/users/paul-buerkner","html_url":"https://github.com/paul-buerkner","followers_url":"https://api.github.com/users/paul-buerkner/followers","following_url":"https://api.github.com/users/paul-buerkner/following{/other_user}","gists_url":"https://api.github.com/users/paul-buerkner/gists{/gist_id}","starred_url":"https://api.github.com/users/paul-buerkner/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/paul-buerkner/subscriptions","organizations_url":"https://api.github.com/users/paul-buerkner/orgs","repos_url":"https://api.github.com/users/paul-buerkner/repos","events_url":"https://api.github.com/users/paul-buerkner/events{/privacy}","received_events_url":"https://api.github.com/users/paul-buerkner/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/paul-buerkner/brms/labels/feature","name":"feature","color":"207de5"}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":9,"created_at":"2016-08-26T22:47:05Z","updated_at":"2016-09-13T08:51:10Z","closed_at":null,"body":"With the implementation of distributional regression in the upcoming release of **brms** 1.0, I think it makes sense to think of additional response distributions (i.e., 'families') that could be worth implementing. Feel free to comment if you would like to see a special response distribution to be added to **brms**  (see also the doc of the **VGAM** package https://cran.r-project.org/web/packages/VGAM/VGAM.pdf for many possible distributions).\r\n\r\n- [ ] Frechet distribution\r\n- [ ] Generalized extreme value distribution\r\n- [ ] Generalized gamma distribution\r\n- [ ] Wiener diffusion model distribution\r\n- [x] von Mises distribution\r\n- [ ] Exponentially modified Gaussian distribution"},"comment":{"url":"https://api.github.com/repos/paul-buerkner/brms/issues/comments/246617122","html_url":"https://github.com/paul-buerkner/brms/issues/110#issuecomment-246617122","issue_url":"https://api.github.com/repos/paul-buerkner/brms/issues/110","id":246617122,"user":{"login":"schmettow","id":1379934,"avatar_url":"https://avatars.githubusercontent.com/u/1379934?v=3","gravatar_id":"","url":"https://api.github.com/users/schmettow","html_url":"https://github.com/schmettow","followers_url":"https://api.github.com/users/schmettow/followers","following_url":"https://api.github.com/users/schmettow/following{/other_user}","gists_url":"https://api.github.com/users/schmettow/gists{/gist_id}","starred_url":"https://api.github.com/users/schmettow/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/schmettow/subscriptions","organizations_url":"https://api.github.com/users/schmettow/orgs","repos_url":"https://api.github.com/users/schmettow/repos","events_url":"https://api.github.com/users/schmettow/events{/privacy}","received_events_url":"https://api.github.com/users/schmettow/received_events","type":"User","site_admin":false},"created_at":"2016-09-13T08:51:10Z","updated_at":"2016-09-13T08:51:10Z","body":"to my knowledge, the exgaussian is a more a pragmatic choice as it seems to fit reaction time data well. There doesn't seem to be a clear match between the two components and cognitive processes (unlike, for example, the shifted Wald, which is tied to the diffusion model in simple choice tasks). In my own research,  I am perfectly fine with mu + lambda. \r\n\r\n--Martin"}}
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