Pareto smoothed importance sampling (PSIS)

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`lw` |
A matrix or vector of log weights. For computing LOO, |

`wcp` |
The proportion of importance weights to use for the generalized
Pareto fit. The |

`wtrunc` |
For truncating very large weights to |

`cores` |
The number of cores to use for parallelization. This can be set
for an entire R session by |

`llfun, llargs` |
See |

`...` |
Ignored when |

See the 'PSIS-LOO' section in `loo-package`

.

A named list with components `lw_smooth`

(modified log weights)
and `pareto_k`

(estimated generalized Pareto shape parameter(s)
*k*).

This function is primarily intended for internal use, but is exported
so that users can call it directly if interested in PSIS for purposes other
than `LOO-CV`

.

Vehtari, A., Gelman, A., and Gabry, J. (2016a). Practical
Bayesian model evaluation using leave-one-out cross-validation and WAIC.
*Statistics and Computing*. Advance online publication.
doi:10.1007/s11222-016-9696-4. arXiv preprint:
http://arxiv.org/abs/1507.04544/

Vehtari, A., Gelman, A., and Gabry, J. (2016b). Pareto smoothed importance sampling. arXiv preprint: http://arxiv.org/abs/1507.02646/

`pareto-k-diagnostic`

for PSIS diagnostics.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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