The posterior package is intended to provide useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to:

• Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions.

• Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws.

• Provide various summaries of draws in convenient formats.

• Provide lightweight implementations of state of the art posterior inference diagnostics.

## Package options

The following options are used to format and print draws objects, as in print.draws_array(), print.draws_df(), print.draws_list(), print.draws_matrix(), and print.draws_rvars():

• posterior.max_draws: Maximum number of draws to print.

• posterior.max_iterations: Maximum number of iterations to print.

• posterior.max_chains: Maximum number of chains to print.

• posterior.max_variables: Maximum number of variables to print.

The following option is used to format and print rvar objects, as in print.rvar() and print.draws_rvars():

• posterior.rvar_summary: What style of summary to display: "mean_sd" displays mean±sd, "median_mad" displays median±mad.

The following option is used to construct new rvar objects, as in rfun() and rdo():

• posterior.rvar_ndraws: The number of draws used to construct new random variables when this number cannot be determined from existing arguments (e.g., other rvars passed to a function).

The following options are used to control warning messages:

• posterior.warn_on_merge_chains: (logical) Some operations will trigger an automatic merging of chains, for example, because chains do not match between two objects involved in a binary operation. Whether this causes a warning can be controlled by this option.