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 extended class of multiplicative row-column (RC) association models,introduced in this paper for two-way contingency tables, allows users to selectboth the type of logit (local, global, continuation, reverse continuation)suitable for the row and column classification variables and the scale on whichinteractions are measured. As in \cite{Kateri95} for the case of local logits,our extended class of bivariate interactions is linked to divergence measuresand, by means of a representation theorem, we provide reconstruction formulasfor the joint probabilities depending on pairs of logit types. These resultsare the key to show that, given marginal logits, our extended interactionsdetermine uniquely the bivariate distribution. We also determine the kind ofpositive association which is implied by our extended interactions being nonnegative. Quick model selection within this wide class can be performed by anefficient algorithm for computing maximum likelihood estimates which exploitsthe properties of a reduced rank constraint imposed on the matrix of extendedinteractions and allows for additional linear constraint on marginal logits. Anapplication to social mobility data is presented and discussed.

An extended class of RC association models: estimation and main properties