3 citations · 5 across the 9 of their papers we have counts for
5 papers · 1 filter
Asymptotic theory for the likelihood-based block maxima method in time series
David L. Carl, Simone A. Padoan, Stefano Rizzelli
This paper develops a rigorous asymptotic framework for likelihood-based inference in the Block Maxima (BM) method for stationary time series. While Bayesian inference under the BM…
Empirical Bayes in Bayesian learning: understanding a common practice
Stefano Rizzelli, Judith Rousseau, Sonia Petrone
In applications of Bayesian procedures, once a class of priors has been chosen, it may be tempting to fix the prior's hyperparameters from the data, in an empirical Bayes (EB) fash…
Asymptotic theory for Bayesian inference and prediction: from the ordinary to a conditional Peaks-Over-Threshold method
Clément Dombry, Simone A. Padoan, Stefano Rizzelli
The Peaks Over Threshold (POT) method is the most popular statistical method for the analysis of univariate extremes. Even though there is a rich applied literature on Bayesian inf…
Marginal expected shortfall inference under multivariate regular variation
Simone A. Padoan, Stefano Rizzelli, Matteo Schiavone
Marginal expected shortfall is unquestionably one of the most popular systemic risk measures. Studying its extreme behaviour is particularly relevant for risk protection against se…
Consistency of Bayesian Inference for Multivariate Max-Stable Distributions
Simone A. Padoan, Stefano Rizzelli
Predicting extreme events is important in many applications in risk analysis. The extreme-value theory suggests modelling extremes by max-stable distributions. The Bayesian approac…