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stat.ME2024
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…
stat.CO2024
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…
stat.ME2024
Markov Switching Multiple-equation Tensor Regressions
Roberto Casarin, Radu Craiu, Qing Wang
We propose a new flexible tensor model for multiple-equation regression that accounts for latent regime changes. The model allows for dynamic coefficients and multi-dimensional cov…