psislw | R Documentation |
As of version 2.0.0
this function is deprecated. Please use the
psis()
function for the new PSIS algorithm.
psislw(
lw,
wcp = 0.2,
wtrunc = 3/4,
cores = getOption("mc.cores", 1),
llfun = NULL,
llargs = NULL,
...
)
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 defaults to
the option |
llfun , llargs |
See |
... |
Ignored when |
A named list with components lw_smooth
(modified log weights) and
pareto_k
(estimated generalized Pareto shape parameter(s) k).
Vehtari, A., Gelman, A., and Gabry, J. (2017). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Statistics and Computing. 27(5), 1413–1432. doi:10.1007/s11222-016-9696-4 (journal version, preprint arXiv:1507.04544).
Vehtari, A., Simpson, D., Gelman, A., Yao, Y., and Gabry, J. (2024). Pareto smoothed importance sampling. Journal of Machine Learning Research, 25(72):1-58. PDF
pareto-k-diagnostic for PSIS diagnostics.
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