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

We introduce a multivariate multidimensional mixed-effects regression modelin a finite mixture framework. We relax the usual unidimensionality assumptionon the random effects multivariate distribution. Thus, we introduce amultidimensional multivariate discrete distribution for the random terms, witha possibly different number of support points in each univariate profile,allowing for a full association structure. Our approach is motivated by theanalysis of economic growth. Accordingly, we define an extended version of theaugmented Solow model. Indeed, we allow all model parameters, and not only themean, to vary according to a regression model. Moreover, we argue thatcountries do not follow the same growth process, and that a mixture-basedapproach can provide a natural framework for the detection of similar growthpatterns. Our empirical findings provide evidence of heterogenous behaviors andsuggest the need of a flexible approach to properly reflect the heterogeneityin the data. We further test the behavior of the proposed approach via asimulation study, considering several factors such as the number of observedunits, times and levels of heterogeneity in the data.

A flexible bivariate location-scale finite mixture approach to economic growth