BayesTools: Provides tools for conducting Bayesian analyses. The package contains functions for creating a wide range of prior distribution objects, mixing posterior samples from JAGS and Stan models, plotting posterior distributions, and etc... The tools for working with prior distribution span from visualization, generating JAGS and bridgesampling syntax to basic functions such as rng, quantile, and distribution functions.
Random-effect operations use the
BayesTools.random_effects_memory_limit_bytes option as a
deterministic pre-allocation guard. The default is 16 * 1024^3
bytes (16 GiB). The estimate includes the primary numeric payload,
simultaneous working copies, row maps, group state, and covariance state
known before allocation. Set a different positive byte ceiling with
options(BayesTools.random_effects_memory_limit_bytes = value).
Experts may explicitly use Inf to disable the guard after verifying
the operation's memory budget. Passing the guard does not promise that an
allocation will succeed because R, JAGS, and the operating system have
additional memory requirements. An operation above the ceiling stops with
an error of class BayesTools_random_effects_memory_limit (also
BayesTools_random_effects_error) whose fields operation,
peak_bytes, and limit_bytes report the estimate.
Useful links: