CmdStanR v0.7.0 released!
This release includes the new Laplace https://mc-stan.org/cmdstanr/reference/model-method-laplace.html and Pathfinder https://mc-stan.org/cmdstanr/reference/model-method-pathfinder.html methods as well as various bug fixes and other new features. See release notes https://github.com/stan-dev/cmdstanr/releases/tag/v0.7.0 for the full list of changes.
Additional support for Pathfinder (e.g., helper functions to convert results into MCMC inits) will follow in the next release.
mc-stan.orgRun Stan's Laplace algorithm — model-method-laplaceThe $laplace() method of a CmdStanModel object produces a
sample from a normal approximation centered at the mode of a distribution
in the unconstrained space. If the mode is a maximum a posteriori (MAP)
estimate, the samples provide an estimate of the mean and standard
deviation of the posterior distribution. If the mode is a maximum
likelihood estimate (MLE), the sample provides an estimate of the standard
error of the likelihood. Whether the mode is the MAP or MLE depends on
the value of the jacobian argument when running optimization. See the
CmdStan User’s Guide
for more details.
Any argument left as NULL will default to the default value used by the
installed version of CmdStan.