6 papers
A general Bayesian bootstrap for censored data based on the beta-Stacy process
Andrea Arfè, Pietro Muliere
We introduce a novel procedure to perform Bayesian non-parametric inference with right-censored data, the \emph{beta-Stacy bootstrap}. This approximates the posterior law of summar…
Conditionally Gaussian Random Sequences for an Integrated Variance Estimator with Correlation between Noise and Returns
Stefano Peluso, Antonietta Mira, Pietro Muliere
Correlation between microstructure noise and latent financial logarithmic returns is an empirically relevant phenomenon with sound theoretical justification. With few notable excep…
The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes
Andrea Arfè, Stefano Peluso, Pietro Muliere
The literature on Bayesian methods for the analysis of discrete-time semi-Markov processes is sparse. In this paper, we introduce the semi-Markov beta-Stacy process, a stochastic p…
Reinforced urns and the subdistribution beta-Stacy process prior for competing risks analysis
Andrea Arfé, Stefano Peluso, Pietro Muliere
In this paper we introduce the subdistribution beta-Stacy process, a novel Bayesian nonparametric process prior for subdistribution functions useful for the analysis of competing r…
International Trade: a Reinforced Urn Network Model
Stefano Peluso, Antonietta Mira, Pietro Muliere +1
We propose a unified modelling framework that theoretically justifies the main empirical regularities characterizing the international trade network. Each country is associated to…
A nonparametric urn-based approach to interacting failing systems with an application to credit risk modeling
Pasquale Cirillo, Jürg Hüsler, Pietro Muliere
In this paper we propose a new nonparametric approach to interacting failing systems (FS), that is systems whose probability of failure is not negligible in a fixed time horizon, a…