Pareto smoothed importance sampling (PSIS) using approximate posteriors
ap_psis(log_ratios, log_p, log_g, ...)# S3 method for array
ap_psis(log_ratios, log_p, log_g, ..., cores = getOption("mc.cores", 1))
# S3 method for matrix
ap_psis(log_ratios, log_p, log_g, ..., cores = getOption("mc.cores", 1))
# S3 method for default
ap_psis(log_ratios, log_p, log_g, ...)
The log-likelihood ratios (ie -log_liks)
The log-posterior (target) evaluated at S samples from the proposal distribution (g). A vector of length S.
The log-density (proposal) evaluated at S samples from the proposal distribution (g). A vector of length S.
Currently not in use.
The number of cores to use for parallelization. This defaults to
the option mc.cores which can be set for an entire R session by
options(mc.cores = NUMBER). The old option loo.cores is now
deprecated but will be given precedence over mc.cores until
loo.cores is removed in a future release. As of version
2.0.0 the default is now 1 core if mc.cores is not set, but we
recommend using as many (or close to as many) cores as possible.
Note for Windows 10 users: it is strongly
recommended to avoid using
the .Rprofile file to set mc.cores (using the cores argument or
setting mc.cores interactively or in a script is fine).
ap_psis(array): An \(I\) by \(C\) by \(N\) array, where \(I\)
is the number of MCMC iterations per chain, \(C\) is the number of
chains, and \(N\) is the number of data points.
ap_psis(matrix): An \(S\) by \(N\) matrix, where \(S\) is the size
of the posterior sample (with all chains merged) and \(N\) is the number
of data points.
ap_psis(default): A vector of length \(S\) (posterior sample size).