Hello, I am new to bayesian statistics and am running brms in R (version 2.21.2) on Windows 10. I have a fairly simple dataset of seedsets of seven different plant species, which I collected from four different elevations on a mountain. I have created pollen limitation indexes from these seedset (…

Hello @Dominik_Anyz , yes I suspect that it will be very difficult to achieve good results from this model without meaningful priors as there is a lot going on and it will want more regularization. You probably should work upwards from the simplest possible representation of this system to understand…

Hi Andrew, thanks for the reply. Although the 0’s and 1’s are imporptant in my research question and tell me in the plants in each elevation were or were not pollen limited, I believe that the ordbetareg package might be exactly what I am looking for. I will give it a go and see.

Hello Robert, thanks for the reply. After a quick read I believe that your package might be the right choice for me. I will read up more on it and try to fit my data into a ordbetareg model.

Hi @saudiwin Robert, so I did try to fit my data into and ordbetareg model, but I have some questions about it. First I would like to ask, is there any way to check the validity/goodness of fit of the model? The reason why I made the original post was that the warnings popped up, however without t…

Hi Dominik - You can use all brms functions for model evaluation, like loo, so see the brms docs for more info. Also the package has a pp_check_ordbeta function for creating posterior predictions that are specific to this model.

Settin priors for unknown data in zero-one inflated beta

Modeling

saudiwin February 26, 2024, 7:07am 3

Yes that is a very top heavy ZOIB parameterization if you have the same linear model for all submodels. Ordbetareg will fit that better – see R package ordbetareg on CRAN (uses brms as a back-end).

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Settin priors for unknown data in zero-one inflated beta

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