10 citations · 27 across the 9 of their papers we have counts for
5 papers · 1 filter
Bayesian dependent mixture models: A predictive comparison and survey
Sara Wade, Vanda Inacio, Sonia Petrone
For exchangeable data, mixture models are an extremely useful tool for density estimation due to their attractive balance between smoothness and flexibility. When additional covari…
Bayesian Time-Varying Tensor Vector Autoregressive Models for Dynamic Effective Connectivity
Wei Zhang, Ivor Cribben, sonia Petrone +1
In contemporary neuroscience, a key area of interest is dynamic effective connectivity, which is crucial for understanding the dynamic interactions and causal relationships between…
Enriched Pitman-Yor processes
Tommaso Rigon, Bruno Scarpa, Sonia Petrone
In Bayesian nonparametrics there exists a rich variety of discrete priors, including the Dirichlet process and its generalizations, which are nowadays well-established tools. Despi…
A closed-form filter for binary time series
Augusto Fasano, Giovanni Rebaudo, Daniele Durante +1
Non-Gaussian state-space models arise in several applications, and within this framework the binary time series setting provides a relevant example. However, unlike for Gaussian st…
Predictive Characterization of Mixtures of Markov Chains
Sandra Fortini, Sonia Petrone
Predictive constructions are a powerful way of characterizing the probability law of stochastic processes with certain forms of invariance, such as exchangeability or Markov exchan…