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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The potential of location-shift models to find adequate models between theproportional odds model and the non-proportional odds model is investigated. Itis demonstrated that these models are very useful in ordinal modeling. Whileproportional odds models are often too simple, non proportional odds models aretypically unnecessary complicated and seem widely dispensable. The class oflocation-shift models is also extended to allow for smooth effects. Theadditive location-shift model contains two functions for each explanatoryvariable, one for the location and one for dispersion. It is much sparser thanhard-to-handle additive models with category-specific covariate functions butmore flexible than common vector generalized additive models.

Non Proportional Odds Models are Widely Dispensable -- Sparser Modeling based on Parametric and Additive Location-Shift Approaches