`adapt_delta.Rd`

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/