English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Determining the sensitivity of the posterior to perturbations of the priorand likelihood is an important part of the Bayesian workflow. We introduce apractical and computationally efficient sensitivity analysis approach usingimportance sampling to estimate properties of posteriors resulting frompower-scaling the prior or likelihood. On this basis, we suggest a diagnosticthat can indicate the presence of prior-data conflict or likelihoodnoninformativity and discuss limitations to this power-scaling approach. Theapproach can be easily included in Bayesian workflows with minimal effort bythe model builder and we present an implementation in our new R packagepriorsense. We further demonstrate the workflow on case studies of real datausing models varying in complexity from simple linear models to Gaussianprocess models.

Detecting and diagnosing prior and likelihood sensitivity with power-scaling