{"action":"created","issue":{"url":"https://api.github.com/repos/hildensia/bayesian_changepoint_detection/issues/2","labels_url":"https://api.github.com/repos/hildensia/bayesian_changepoint_detection/issues/2/labels{/name}","comments_url":"https://api.github.com/repos/hildensia/bayesian_changepoint_detection/issues/2/comments","events_url":"https://api.github.com/repos/hildensia/bayesian_changepoint_detection/issues/2/events","html_url":"https://github.com/hildensia/bayesian_changepoint_detection/issues/2","id":81065986,"number":2,"title":"Other observation models besides Gaussian","user":{"login":"mathDR","id":2363269,"avatar_url":"https://avatars.githubusercontent.com/u/2363269?v=3","gravatar_id":"","url":"https://api.github.com/users/mathDR","html_url":"https://github.com/mathDR","followers_url":"https://api.github.com/users/mathDR/followers","following_url":"https://api.github.com/users/mathDR/following{/other_user}","gists_url":"https://api.github.com/users/mathDR/gists{/gist_id}","starred_url":"https://api.github.com/users/mathDR/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mathDR/subscriptions","organizations_url":"https://api.github.com/users/mathDR/orgs","repos_url":"https://api.github.com/users/mathDR/repos","events_url":"https://api.github.com/users/mathDR/events{/privacy}","received_events_url":"https://api.github.com/users/mathDR/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/hildensia/bayesian_changepoint_detection/labels/enhancement","name":"enhancement","color":"84b6eb"}],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":10,"created_at":"2015-05-26T17:45:50Z","updated_at":"2015-06-10T23:57:08Z","closed_at":null,"body":"Hi.  I was wondering if you had any insight in extending your code to include other emission models besides gaussian.  In particular, how about a GMM with known number of gaussians?\r\n\r\nI was going to take a stab at implementing it and submit a PR, but wanted to get your input first.\r\n\r\nThanks\r\n\r\nDan"},"comment":{"url":"https://api.github.com/repos/hildensia/bayesian_changepoint_detection/issues/comments/110949480","html_url":"https://github.com/hildensia/bayesian_changepoint_detection/issues/2#issuecomment-110949480","issue_url":"https://api.github.com/repos/hildensia/bayesian_changepoint_detection/issues/2","id":110949480,"user":{"login":"mathDR","id":2363269,"avatar_url":"https://avatars.githubusercontent.com/u/2363269?v=3","gravatar_id":"","url":"https://api.github.com/users/mathDR","html_url":"https://github.com/mathDR","followers_url":"https://api.github.com/users/mathDR/followers","following_url":"https://api.github.com/users/mathDR/following{/other_user}","gists_url":"https://api.github.com/users/mathDR/gists{/gist_id}","starred_url":"https://api.github.com/users/mathDR/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mathDR/subscriptions","organizations_url":"https://api.github.com/users/mathDR/orgs","repos_url":"https://api.github.com/users/mathDR/repos","events_url":"https://api.github.com/users/mathDR/events{/privacy}","received_events_url":"https://api.github.com/users/mathDR/received_events","type":"User","site_admin":false},"created_at":"2015-06-10T23:57:08Z","updated_at":"2015-06-10T23:57:08Z","body":"Upon looking at section 3.4 of the Xuan paper, I am drawing a blank as to what the default mean basis should be (the H in the paper).  I am leaning towards 1, but then I don't know what D then becomes.  Any thoughts?"}}