3 сент. 2021 г. · Operating System: Mac brms Version: 2.16.1 Since updating to brms 2.16.1, I'm having difficulty using adapt_delta.

22 сент. 2020 г. · I want to be able to reject bootstrap models with divergent transitions and to refit them with a higher adapt_delta until there are no divergences.

" you should really think about increasing adapt_delta. To do this, write control = list(adapt_delta = <x>), where <x> should usually be value between 0.8 ...

Increasing adapt_delta will slow down the sampler but will decrease the number of divergent transitions threatening the validity of your posterior samples.

The Stan control argument adapt_delta sets the target average acceptance probability for the No-U-Turn Sampler (NUTS) used by Stan.

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 (non-)linear multivariate multilevel models using Stan, which is a C++ package for ...

It is true that I get less "divergent transitions" when I increase adapt_delta . What does it mean ? Even when I increase it to 0.98 I still get "divergent ...

Fit Bayesian generalized (non-)linear multivariate multilevel models using Stan for full Bayesian inference. A wide range of distributions and link functions ... Arguments · Details

6 авг. 2022 г. · I get Warning: There were 40 divergent transitions after warmup. Increasing adapt_delta above may help. See http://mc-stan.org/misc/warnings.