5 citations · 12 across the 19 of their papers we have counts for
12 papers · 1 filter
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 Markov-Switching Partial Reduced-Rank Regression
Maria F. Pintado, Matteo Iacopini, Luca Rossini +1
Reduced-Rank (RR) regression is a powerful dimensionality reduction technique but it overlooks any possible group configuration among the responses by assuming a low-rank structure…
Bayesian Partial Reduced-Rank Regression
Maria F. Pintado, Matteo Iacopini, Luca Rossini +1
Reduced-rank (RR) regression may be interpreted as a dimensionality reduction technique able to reveal complex relationships among the data parsimoniously. However, RR regression m…
Static and Dynamic BART for Rank-Order Data
Matteo Iacopini, Eoghan O'Neill, Luca Rossini
Ranking lists are often provided at regular time intervals in a range of applications, including economics, sports, marketing, and politics. Most popular methods for rank-order dat…
A Spatiotemporal Gamma Shot Noise Cox Process
Federico Bassetti, Roberto Casarin, Matteo Iacopini +1
A new discrete-time shot noise Cox process for spatiotemporal data is proposed. The random intensity is driven by a dependent sequence of latent gamma random measures. Some propert…
Uncertainty Quantification in Bayesian Reduced-Rank Sparse Regressions
Maria F. Pintado, Matteo Iacopini, Luca Rossini +1
Reduced-rank regression recognises the possibility of a rank-deficient matrix of coefficients. We propose a novel Bayesian model for estimating the rank of the coefficient matrix,…
Visualizing and comparing distributions with half-disk density strips
Carlo Romano Marcello Alessandro Santagiustina, Matteo Iacopini
We propose a user-friendly graphical tool, the half-disk density strip (HDDS), for visualizing and comparing probability density functions. The HDDS exploits color shading for repr…
Proper scoring rules for evaluating asymmetry in density forecasting
Matteo Iacopini, Francesco Ravazzolo, Luca Rossini
This paper proposes a novel asymmetric continuous probabilistic score (ACPS) for evaluating and comparing density forecasts. It extends the proposed score and defines a weighted ve…
Nonparametric forecasting of multivariate probability density functions
Dominque Guégan, Matteo Iacopini
The study of dependence between random variables is the core of theoretical and applied statistics. Static and dynamic copula models are useful for describing the dependence struct…
Bayesian Markov Switching Tensor Regression for Time-varying Networks
Monica Billio, Roberto Casarin, Matteo Iacopini
We propose a new Bayesian Markov switching regression model for multidimensional arrays (tensors) of binary time series. We assume a zero-inflated logit regression with time-varyin…
Bayesian Dynamic Tensor Regression
Monica Billio, Roberto Casarin, Matteo Iacopini +1
Tensor-valued data are becoming increasingly available in economics and this calls for suitable econometric tools. We propose a new dynamic linear model for tensor-valued response…
Discussion on "Sparse graphs using exchangeable random measures" by F. Caron and E. B. Fox
Roberto Casarin, Matteo Iacopini, Luca Rossini
Discussion on "Sparse graphs using exchangeable random measures" by F. Caron and E. B. Fox. In this discussion we contribute to the analysis of the GGP model as compared to the Erd…