Set and read options used in RStan. Some settings as options can be controlled by the user.
rstan_options(...)The values as a list for existing options and NA for non-existent options.
When only one option is specified, its old value is returned.
Arguments of the form opt = val set
option opt to value val. Arguments of the
form opt set the function to return option opt's value.
Each argument must be a character string.
The available options are:
plot_rhat_breaks: The cut off points for Rhat for which we
would indicate using a different color. This is a numeric vector,
defaulting to c(1.1, 1.2, 1.5, 2).
The value for this option will be sorted in ascending order,
so for example plot_rhat_breaks = c(1.2, 1.5) is equivalent to
plot_rhat_breaks = c(1.5, 1.2).
plot_rhat_cols: A vector of the same length as
plot_rhat_breaks that indicates the colors for the
breaks.
plot_rhat_nan_col: The color for Rhat when it is Inf or NaN.
plot_rhat_large_col: The color for Rhat when it is larger than
the largest value of plot_rhat_breaks.
rstan_alert_col: The color used in method plot
of S4 class stanfit to show that the vector/array
parameters are truncated.
rstan_chain_cols: The colors used in methods plot
and traceplot of S4 class stanfit
for coloring different chains.
rstan_warmup_bg_col: The background color for
the warmup area in the traceplots.
boost_lib: The path for the Boost C++ library used
to compile Stan models. This option is valid
for the whole R session if not changed again.
eigen_lib: The path for the Eigen C++ library used
to compile Stan models. This option is valid
for the whole R session if not changed again.
auto_write: A logical scalar (defaulting to FALSE) that
controls whether a compiled instance of a stanmodel-class
is written to the hard disk in the same directory as the .stan
program.
threads_per_chain: A positive integer (defaulting to 1).
If the model was compiled with threading support, the number of
threads to use in parallelized sections _within_ an MCMC chain (e.g., when
using the Stan functions `reduce_sum()` or `map_rect()`). The actual number of CPU cores
used is `chains * threads_per_chain` where `chains` is the number of parallel chains.
For an example of using threading, see the Stan case study [Reduce Sum: A Minimal
Example](https://mc-stan.org/users/documentation/case-studies/reduce_sum_tutorial.html).