Autori: Liseo, Brunero , Doroshenko, Lyubov
Titolo: Generalized linear mixed model with bayesian rank likelihood
Periodico: Statistical methods & applications : Journal of the Italian Statistical Society
Anno: 2023 - Volume: 32 - Fascicolo: 2 - Pagina iniziale: 425 - Pagina finale: 446

We consider situations where a model for an ordered categorical response variable is deemed necessary. Standard models may not be suited to perform this analysis, being that the marginal probability effects to a large extent are predetermined by the rigid parametric structure. We propose to use a rank likelihood approach in a non Gaussian framework and show how additional flexibility can be gained by modeling individual heterogeneity in terms of latent structure. This approach avoids to set a specific link between the observed categories and the latent quantities and it is discussed in the broadly general case of longitudinal data. A real data example is illustrated in the context of sovereign credit ratings modeling and forecasting.


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SICI: 1618-2510(2023)32:2<425:GLMMWB>2.0.ZU;2-U

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