From df5a46bd2db8c9b8bae33be76d156e78cf870217 Mon Sep 17 00:00:00 2001 From: Alexandre Courtiol Date: Sun, 7 Mar 2021 16:45:58 +0100 Subject: [PATCH] Add glmmTMB fit --- vignettes/spaMM.rmd | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/vignettes/spaMM.rmd b/vignettes/spaMM.rmd index c388c8a..64e5593 100644 --- a/vignettes/spaMM.rmd +++ b/vignettes/spaMM.rmd @@ -116,8 +116,9 @@ These cases do not seem to be handled properly $\rightarrow$ the question is whe ## Poisson GLM ### Fitting models -```{r glm_pos} +```{r glm_pos, warning=FALSE} glm_pois_log_glm <- glm(total.fruits ~ amd, family = poisson(link = "log"), data = Arabidopsis) +glm_pois_log_glmmTMB <- glmmTMB(total.fruits ~ amd, family = poisson(link = "log"), data = Arabidopsis) glm_pois_log_fitme <- fitme(total.fruits ~ amd, family = poisson(link = "log"), data = Arabidopsis) ``` @@ -130,13 +131,14 @@ TO COME ### Outputs from `glance()` ```{r glance glm_pos} glance(glm_pois_log_glm) +glance(glm_pois_log_glmmTMB) glance(glm_pois_log_fitme) ``` #### Fixme? - `glance.glm()` compares the model to a null model, albeit with no test $\rightarrow$ shall we do that? -- again, we could drop the column `sigma` but perhaps it is best to keep it for enforcing a consistent output +- again, we could drop the column `sigma` but perhaps it is best to keep it for enforcing a consistent output, or as `glance.glmmTMB()` we could indicate overdispersion as `sigma` (nb: they did not document that)...? ## Binomial GLM