{"action":"created","issue":{"url":"https://api.github.com/repos/spatstat/spatstat/issues/8","labels_url":"https://api.github.com/repos/spatstat/spatstat/issues/8/labels{/name}","comments_url":"https://api.github.com/repos/spatstat/spatstat/issues/8/comments","events_url":"https://api.github.com/repos/spatstat/spatstat/issues/8/events","html_url":"https://github.com/spatstat/spatstat/issues/8","id":76205032,"number":8,"title":"parres() function --- `Fitting algorithm for ‘glm’ did not converge` warning","user":{"login":"elgabbas","id":7375051,"avatar_url":"https://avatars.githubusercontent.com/u/7375051?v=3","gravatar_id":"","url":"https://api.github.com/users/elgabbas","html_url":"https://github.com/elgabbas","followers_url":"https://api.github.com/users/elgabbas/followers","following_url":"https://api.github.com/users/elgabbas/following{/other_user}","gists_url":"https://api.github.com/users/elgabbas/gists{/gist_id}","starred_url":"https://api.github.com/users/elgabbas/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/elgabbas/subscriptions","organizations_url":"https://api.github.com/users/elgabbas/orgs","repos_url":"https://api.github.com/users/elgabbas/repos","events_url":"https://api.github.com/users/elgabbas/events{/privacy}","received_events_url":"https://api.github.com/users/elgabbas/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":4,"created_at":"2015-05-14T02:40:56Z","updated_at":"2015-06-26T14:00:49Z","closed_at":"2015-06-26T14:00:48Z","body":"Hello all,\r\n\r\nI am having a problem with the `parres()` function, with a ppm model having interactions between covariates.\r\n\r\nI am receiving an error like:\r\n`\tError in parres(model = CurrPPM, covariate = \"Var1\")`\r\n`\tThe covariate ‘Var1’ cannot be separated from the covariates ‘Var2’ and ‘Var3’ in the model terms ‘Var1:Var2’ and ‘Var1:Var3’`\r\n\r\nWhile running the ppm model, I've used a formula like: ` as.formula(~(Var + Var2 + Var3)^2 + I(Var1^2) + I(Var2^2) + I(Var3^2))` to include all variables, their quadratic terms and all possible combinations. Then I've used the `MASS:::stepAIC()` function to select the best model out of the initial model. When I am trying to do some model diagnostics, it works fine except for the `parres()` function. The covariates were provided to the model as original variables, and I am using the formula mentioned above to include the interactions on the fly while running the model. i.e. I provided just a list of 3 real-valued pixel image (class: `im`) not the interactions or the quadratic terms and they were calculated properly while running the model. Is that the cause of the error message I am receiving? Should I prepare, as much as I need, real-valued pixel images (`im`) of the interactions and quadratic terms and provide them explicitly as covariates?\r\n\r\nAnother thing, I am always receiving a warning message of: ` *** Fitting algorithm for ‘glm’ did not converge ***` even if the model takes somehow much time to process. I've tried to use something like: `glm.control(maxit = 1000)` but it does not help much. Is it ok to ignore this warning message? or I should do some other steps to avoid such warnings? In one of my cases, there is `81` points and `590083` dummy points. Is the number of points not enough to run a reasonable ppm model compared to the used number of dummy points?\r\n\r\nThanks,\r\nAhmed"},"comment":{"url":"https://api.github.com/repos/spatstat/spatstat/issues/comments/115699305","html_url":"https://github.com/spatstat/spatstat/issues/8#issuecomment-115699305","issue_url":"https://api.github.com/repos/spatstat/spatstat/issues/8","id":115699305,"user":{"login":"elgabbas","id":7375051,"avatar_url":"https://avatars.githubusercontent.com/u/7375051?v=3","gravatar_id":"","url":"https://api.github.com/users/elgabbas","html_url":"https://github.com/elgabbas","followers_url":"https://api.github.com/users/elgabbas/followers","following_url":"https://api.github.com/users/elgabbas/following{/other_user}","gists_url":"https://api.github.com/users/elgabbas/gists{/gist_id}","starred_url":"https://api.github.com/users/elgabbas/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/elgabbas/subscriptions","organizations_url":"https://api.github.com/users/elgabbas/orgs","repos_url":"https://api.github.com/users/elgabbas/repos","events_url":"https://api.github.com/users/elgabbas/events{/privacy}","received_events_url":"https://api.github.com/users/elgabbas/received_events","type":"User","site_admin":false},"created_at":"2015-06-26T14:00:48Z","updated_at":"2015-06-26T14:00:48Z","body":"Yes, it was helpful..\r\nActually, I have to say earlier: thanks for the reply, but so far I've not applied that so I am not sure if I will face simillar issue again.\r\nI will close this issue, and in the case of extra comment/s I will re-open it again.\r\nThanks, Ahmed"}}