{"action":"opened","issue":{"url":"https://api.github.com/repos/p2t2/figaro/issues/581","repository_url":"https://api.github.com/repos/p2t2/figaro","labels_url":"https://api.github.com/repos/p2t2/figaro/issues/581/labels{/name}","comments_url":"https://api.github.com/repos/p2t2/figaro/issues/581/comments","events_url":"https://api.github.com/repos/p2t2/figaro/issues/581/events","html_url":"https://github.com/p2t2/figaro/issues/581","id":157243914,"number":581,"title":"Kernel density estimator element","user":{"login":"dgarant","id":1395768,"avatar_url":"https://avatars.githubusercontent.com/u/1395768?v=3","gravatar_id":"","url":"https://api.github.com/users/dgarant","html_url":"https://github.com/dgarant","followers_url":"https://api.github.com/users/dgarant/followers","following_url":"https://api.github.com/users/dgarant/following{/other_user}","gists_url":"https://api.github.com/users/dgarant/gists{/gist_id}","starred_url":"https://api.github.com/users/dgarant/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/dgarant/subscriptions","organizations_url":"https://api.github.com/users/dgarant/orgs","repos_url":"https://api.github.com/users/dgarant/repos","events_url":"https://api.github.com/users/dgarant/events{/privacy}","received_events_url":"https://api.github.com/users/dgarant/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2016-05-27T16:27:36Z","updated_at":"2016-05-27T16:27:36Z","closed_at":null,"body":"It would be useful to employ kernel density estimators when a reasonable parametric model cannot be selected. I have added a simple univariate KDE which employs the Gaussian kernel, see pull request #580."}}
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