10 citations · 27 across the 9 of their papers we have counts for
11 papers
Nonparametric quantile inference using Dirichlet processes
Nils Lid Hjort, Sonia Petrone
This chapter deals with nonparametric inference for quantiles from a Bayesian perspective, using the Dirichlet process. The posterior distribution for quantiles is characterised, e…
Exchangeability, prediction and predictive modeling in Bayesian statistics
Sandra Fortini, Sonia Petrone
There is currently a renewed interest in the Bayesian predictive approach to statistics. This paper offers a review on foundational concepts and focuses on predictive modeling, whi…
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…
Infinite-color randomly reinforced urns with dominant colors
Hristo Sariev, Sandra Fortini, Sonia Petrone
We define and prove limit results for a class of dominant Pólya sequences, which are randomly reinforced urn processes with color-specific random weights and unbounded number of po…
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…
Quasi-Bayes properties of a recursive procedure for mixtures
Sandra Fortini, Sonia Petrone
Bayesian methods are often optimal, yet increasing pressure for fast computations, especially with streaming data, brings renewed interest in faster, possibly sub-optimal, solution…
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…
On a notion of partially conditionally identically distributed sequences
Sandra Fortini, Sonia Petrone, Polina Sporysheva
A notion of conditionally identically distributed (c.i.d.) sequences has been studied as a form of stochastic dependence that is weaker than exchangeability, but is equivalent to e…
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…
Bayes and empirical Bayes: do they merge?
Sonia Petrone, Judith Rousseau, Catia Scricciolo
Bayesian inference is attractive for its coherence and good frequentist properties. However, it is a common experience that eliciting a honest prior may be difficult and, in practi…