{"action":"created","issue":{"url":"https://api.github.com/repos/paul-buerkner/brms/issues/86","repository_url":"https://api.github.com/repos/paul-buerkner/brms","labels_url":"https://api.github.com/repos/paul-buerkner/brms/issues/86/labels{/name}","comments_url":"https://api.github.com/repos/paul-buerkner/brms/issues/86/comments","events_url":"https://api.github.com/repos/paul-buerkner/brms/issues/86/events","html_url":"https://github.com/paul-buerkner/brms/issues/86","id":161821423,"number":86,"title":"Setting upper/lower bounds separately for each covariate","user":{"login":"alireza202","id":6646274,"avatar_url":"https://avatars.githubusercontent.com/u/6646274?v=3","gravatar_id":"","url":"https://api.github.com/users/alireza202","html_url":"https://github.com/alireza202","followers_url":"https://api.github.com/users/alireza202/followers","following_url":"https://api.github.com/users/alireza202/following{/other_user}","gists_url":"https://api.github.com/users/alireza202/gists{/gist_id}","starred_url":"https://api.github.com/users/alireza202/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/alireza202/subscriptions","organizations_url":"https://api.github.com/users/alireza202/orgs","repos_url":"https://api.github.com/users/alireza202/repos","events_url":"https://api.github.com/users/alireza202/events{/privacy}","received_events_url":"https://api.github.com/users/alireza202/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/paul-buerkner/brms/labels/question","name":"question","color":"cc317c"}],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":9,"created_at":"2016-06-23T01:27:18Z","updated_at":"2016-07-08T21:01:43Z","closed_at":"2016-07-06T00:56:36Z","body":"I tried doing:\r\n\r\n```\r\npriors = c(set_prior('normal(0, 10)', class = 'b', coef = 'x', ub = 0),\r\n           set_prior('normal(0, 10)', class = 'b', coef = 'y', ub = 3))\r\n```\r\nwhere `x` and `y` are two covariates, but I got the error:\r\n\r\n```\r\n'coef' may not be specified when using boundaries\r\n```\r\nIs there really noway to do this?"},"comment":{"url":"https://api.github.com/repos/paul-buerkner/brms/issues/comments/231471767","html_url":"https://github.com/paul-buerkner/brms/issues/86#issuecomment-231471767","issue_url":"https://api.github.com/repos/paul-buerkner/brms/issues/86","id":231471767,"user":{"login":"alireza202","id":6646274,"avatar_url":"https://avatars.githubusercontent.com/u/6646274?v=3","gravatar_id":"","url":"https://api.github.com/users/alireza202","html_url":"https://github.com/alireza202","followers_url":"https://api.github.com/users/alireza202/followers","following_url":"https://api.github.com/users/alireza202/following{/other_user}","gists_url":"https://api.github.com/users/alireza202/gists{/gist_id}","starred_url":"https://api.github.com/users/alireza202/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/alireza202/subscriptions","organizations_url":"https://api.github.com/users/alireza202/orgs","repos_url":"https://api.github.com/users/alireza202/repos","events_url":"https://api.github.com/users/alireza202/events{/privacy}","received_events_url":"https://api.github.com/users/alireza202/received_events","type":"User","site_admin":false},"created_at":"2016-07-08T21:01:43Z","updated_at":"2016-07-08T21:01:43Z","body":"I understand that in general, this is not a good idea. But in my problem, I have cases where the item is showing a behavior that is logically impossible, and the reason is that there are variables that I can't take into account, and I don't know about, and these result in the illogical behavior that I see. \r\n\r\nOne strategy to deal with these is to remove that item's specific random effect variable (in the above example, `z ~ x + y + x | item` the random effect `x`) and only use the fixed effect for it. Note that I don't want to remove random effect for the intercept, but just the covariate. \r\n\r\nI know this is very specific, and you probably don't want to implement it, but if I can make a hack myself, it would be great. Any pointers on how to do this? Would it make sense to identify these items after the fit, and run a separate `predict` function with a modified `re.formula`, for example `re.formula = ~ 1 | item`?"}}
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