Paul-Christian Bürkner

Results 30 issues of Paul-Christian Bürkner

#### Summary: Allow `_lupdf` and `_lupmf` in the transformed parameters block. #### Description: For implementing prior sensitivity checks via power scaling (https://arxiv.org/abs/2107.14054; a paper together with @avehtari), we need to...

With the implementation of several new features in the upcoming **brms** 1.3.0 release, some more vignettes are required to explain certain aspects of the package in detail. - [x] Multilevel...

documentation
good first issue

The Conway-Maxwell-Poisson distribution (https://en.wikipedia.org/wiki/Conway%E2%80%93Maxwell%E2%80%93Poisson_distribution) is a generalization of the Poisson distribution that allows for both over- and underdispersion. There have been some attempts to get this distribution running in Stan,...

feature
family
good first issue

Currently, the Stan code of a multilevel models looks a little verbose due to first indexing columns and then looping over observations to select the right elements of the computed...

efficiency
feature

On twitter, Andrew McDonald suggested writing a cheat sheet for brms similar to how it is done for many other packages and I agree (e.g., see the cheat sheets of...

documentation
good first issue

Right now, only the exponentiated-quadratic kernel is supported as it has a native implementation in Stan. However, there seem to be quite a few other kernels worth considering. This issue...

feature
formula
good first issue

The generalized poisson distribution has some potential when it comes to the estimation of underdispersed count data and is much more efficient to evaluate the the conway-maxwell poisson distribution. It...

feature
family
good first issue

This should reduce the number of duplicated documentation snippets and replace `@inheritParams` tags.

documentation
good first issue

Currently, brmsfit objects store some information multiple times at different places to retain backwards compatibility with older versions of brms. In version 3.0 (still a long way to go), we...

objects