E_loo
function for computing weighted expectations (means, variances, quantiles).pareto_k_table
and pareto_k_ids
convenience functions for quickly identifying problematic observations(-Inf, 0.5]
, (0.5, 0.7]
, (0.7, 1]
, (1, Inf)
(didn't used to include 0.7)psislw
instead of print.loo
print.loo
shows a table of pareto k estimates (if any k > 0.7)compare
to allow loo objects to be provided in a list rather than in '...'
extract_log_lik
compare
. compare
. We have removed the weights because they were based only on the point estimate of the elpd values ignoring the uncertainty. We are currently working on something similar to these weights that also accounts for uncertainty, which will be included in future versions of loo.This update makes it easier for other package authors using loo to write tests that involve running the loo
function. It also includes minor bug fixes and additional unit tests. Highlights:
cores=1
.psislw
function is called in an interactive session.This update provides several important improvements, most notably an alternative method for specifying the pointwise log-likelihood that reduces memory usage and allows for loo to be used with larger datasets. This update also makes it easier to to incorporate loo's functionality into other packages.
matrix
and function
methods for both loo
and waic
. The matrix method provide the same functionality as in previous versions of loo (taking a log-likelihood matrix as the input). The function method allows the user to provide a function for computing the log-likelihood from the data and posterior draws (which are also provided by the user). The function method is less memory intensive and should make it possible to use loo for models fit to larger amounts of data than before.plot
and print
methods. plot
also provides label_points
argument, which, if TRUE
, will label any Pareto k
points greater than 1/2 by the index number of the corresponding observation. The plot method also now warns about Inf
/NA
/NaN
values of k
that are not shown in the plot.compare
now returns model weights and accepts more than two inputs.options(loo.cores = NUMBER)
.loo_and_waic
function in favor of separate functions loo
and waic
loo_and_waic_diff
. Use compare
instead.