23 сент. 2024 г. · brms: Bayesian Regression Models using 'Stan'. Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full ...

The brms package provides an interface to fit Bayesian generalized (non-)linear multivariate multilevel models using Stan, which is a C++ package for ...

The brms package implements Bayesian multilevel models in R using the probabilis- tic programming language Stan. A wide range of distributions and link ...

The following tutorial is an introduction to Bayesian modelling but it assumes a prior understanding of modelling and data distribution.

The brms package provides an interface to fit Bayesian generalized multivariate (non-)linear multilevel models using Stan, which is a C++ package for obtaining ...

29 авг. 2017 г. · The brms package implements Bayesian multilevel models in R using the probabilistic programming language Stan. A wide range of distributions ...

The brms package provides a flexible interface to fit Bayesian generalized (non)linear multivariate multilevel models using Stan.

The \pkg{brms} package provides an interface to fit Bayesian generalized multivariate (non-)linear multilevel models using \pkg{Stan}, which is a C++ package.

Can be controlled globally for the current R session via the `brms.normalize` option. control. A named list of parameters to control the sampler's behavior. It ...

Introduction. When you fit a model with brms, the package calls Rstan which is an R interface to the statistical programming language Stan.