5 papers
Generalized Poisson Dynamic Network Models
Giulia Carallo, Roberto Casarin, Antonio Peruzzi
Count-weighted temporal networks often exhibit unequal dispersion in the edge weights, which cannot be fully explained by modelling observational heterogeneity through latent facto…
A Bayesian Dynamic Latent Space Model for Weighted Networks
Roberto Casarin, Matteo Iacopini, Antonio Peruzzi
A new dynamic latent space eigenmodel (LSM) is proposed for weighted temporal networks. The model accommodates integer-valued weights, excess of zeros, time-varying node positions…
Bayesian Outlier Detection for Matrix-variate Models
Monica Billio, Roberto Casarin, Fausto Corradin +1
Anomalies in economic and financial data -- often linked to rare yet impactful events -- are of theoretical interest, but can also severely distort inference. Although outlier-robu…
Comment on 'Sparse Bayesian Factor Analysis when the Number of Factors is Unknown' by S. Frühwirth-Schnatter, D. Hosszejni, and H. Freitas Lopes
Roberto Casarin, Antonio Peruzzi
The techniques suggested in Frühwirth-Schnatter et al. (2024) concern sparsity and factor selection and have enormous potential beyond standard factor analysis applications. We sho…
A Multiple Random Scan Strategy for Latent Space Models
Roberto Casarin, Antonio Peruzzi
Latent Space (LS) network models project the nodes of a network on a -dimensional latent space to achieve dimensionality reduction of the network while preserving its relevant f…