Details about the adapt_delta argument to rstanarm's modeling
functions.
For the No-U-Turn Sampler (NUTS), the variant of Hamiltonian Monte
Carlo used used by rstanarm, adapt_delta is the target average
proposal acceptance probability for adaptation. adapt_delta is
ignored if algorithm is not "sampling".
The default value of adapt_delta is 0.95, except when the prior for
the regression coefficients is R2, hs, or
hs_plus, in which case the default is 0.99.
In general you should not need to change adapt_delta unless you see
a warning message about divergent transitions, in which case you can
increase adapt_delta from the default to a value closer to 1
(e.g. from 0.95 to 0.99, or from 0.99 to 0.999, etc). The step size used by
the numerical integrator is a function of adapt_delta in that
increasing adapt_delta will result in a smaller step size and fewer
divergences. Increasing adapt_delta will typically result in a
slower sampler, but it will always lead to a more robust sampler.
Stan Development Team. (2017). Stan Modeling Language Users Guide and Reference Manual. http://mc-stan.org/documentation/