After a review of the class of discrete latent variable models in terms of formulation and estimation methods, recent advances and perspectives regarding these models are illustrated. We consider in detail the stochastic block model for social networks and models for spatio-temporal data. Among these developments, we discuss, in particular, the analysis of longitudinal compositional data about expenditures of the Spanish regions over several decades.
Bartolucci, F., Greenacre, M., Pandolfi, S., Pennoni, F. (2023). Discrete latent variable models: Recent and advances and perspectives. In P. Coretto, G. Giordano, M. La Rocca, M.L. Parrella, C. Rampichini (a cura di), CLADAG 2023 Book of Abstract and Short Papers. 14th Scientific Meeting of the Classification and Data Analysis Group, Salerno, September 11-13, 2023 (pp. 3-6). Milano : Pearson Education Resources.
Discrete latent variable models: Recent and advances and perspectives
Pennoni, F
2023
Abstract
After a review of the class of discrete latent variable models in terms of formulation and estimation methods, recent advances and perspectives regarding these models are illustrated. We consider in detail the stochastic block model for social networks and models for spatio-temporal data. Among these developments, we discuss, in particular, the analysis of longitudinal compositional data about expenditures of the Spanish regions over several decades.File | Dimensione | Formato | |
---|---|---|---|
Bartolucci-2023-CLADAG 2023 Book of Abstract Short Papers-VoR.pdf
Solo gestori archivio
Descrizione: Contributo in libro
Tipologia di allegato:
Publisher’s Version (Version of Record, VoR)
Licenza:
Tutti i diritti riservati
Dimensione
901.22 kB
Formato
Adobe PDF
|
901.22 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.