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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In this paper we consider Poisson loglinear models with linear constraints(LMLC) on the expected table counts. Multinomial and product multinomialloglinear models can be obtained by considering that some marginal totals(linear constraints on the expected table counts) have been prefixed in aPoisson loglinear model. Therefore with the theory developed in this paper,multinomial and product multinomial loglinear models can be considered as aparticular case. To carry out inferences on the parameters in the LMLC aninformation-theoretic approach is followed from which the classical maximumlikelihood estimators and Pearson chi-square statistics for goodness-of fit areobtained. In addition, nested hypotheses are proposed as a general procedurefor hypothesis testing. Through a simulation study the appropriateness ofproposed inference tools is illustrated.

Poisson loglinear modeling with linear constraints on the expected cell frequencies