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math.ST2026

Some cautionary tales about Bayesian predictive inference

Emanuela Dreassi, Fabrizio Leisen, Luca Pratelli +1

Two misunderstandings, frequently arising in Bayesian predictive inference, are discussed. The first deals with the data generating mechanism, while the second consists in overesti…

math.ST2025

Estimation and goodness-of-fit testing for non-negative random variables with explicit Laplace transform

Lucio Barabesi, Antonio Di Noia, Marzia Marcheselli +2

Many flexible families of positive random variables exhibit non-closed forms of the density and distribution functions and this feature is considered unappealing for modelling purp…

math.ST2024

Knockoffs for exchangeable categorical covariates

Emanuela Dreassi, Luca Pratelli, Pietro Rigo

Let be a -variate random vector and a fixed finite set. In a number of applications, mainly in genetics, it turns out that for each $i=1,\ldo…

math.ST2024

Censoring heavy-tail count distributions for parameter estimation with an application to stable distributions

Antonio Di Noia, Marzia Marcheselli, Caterina Pisani +1

A new approach based on censoring and moment criterion is introduced for parameter estimation of count distributions when the probability generating function is available even thou…

math.ST2024

Asymptotics of predictive distributions driven by sample means and variances

Samuele Garelli, Fabrizio Leisen, Luca Pratelli +1

Let be the predictive distributions of a sequence of -dimensional random vectors. Suppose $$α_n…

math.ST2024

A family of consistent normally distributed tests for Poissonity

Antonio Di Noia, Marzia Marcheselli, Caterina Pisani +1

A family of consistent tests, derived from a characterization of the probability generating function, is proposed for assessing Poissonity against a wide class of count distributio…