Aggregate PSIS-LOO summaries can be read together with observation-level predictive contributions and influence diagnostics.
atlas <- create_loo_influence_atlas(
loo_result,
data = fit$specification$prepared$data
)
loo_influence_summary(atlas$table)
loo_flagged_data(atlas$table)
plot_loo_pointwise_elpd(atlas$table)
plot_loo_pareto_vs_elpd(atlas$table)
plot_loo_influence_rank(atlas$table)Flagged observations request inspection and are never removed automatically.
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.