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20212025
most citedGoodness-of-fit test for count distributions with finite second moment

5 citations · 11 across the 10 of their papers we have counts for

collaborators

10 papers

math.ST2025

Deconvolution in unlinked linear models

Fadoua Balabdaoui, Antonio Di Noia, Cécile Durot

Unlinked regression, in which covariates and responses are observed separately without known correspondence, has recently gained increasing attention. Deconvolution, on the other h…

stat.ML2025

A general framework for adaptive nonparametric dimensionality reduction

Antonio Di Noia, Federico Ravenda, Antonietta Mira

Dimensionality reduction is a fundamental task in modern data science. Several projection methods specifically tailored to take into account the non-linearity of the data via local…

math.ST2024

Asymptotic theory for nonparametric testing of -monotonicity in discrete distributions

Fadoua Balabdaoui, Antonio Di Noia

In shape-constrained nonparametric inference, it is often necessary to perform preliminary tests to verify whether a probability mass function (p.m.f.) satisfies qualitative constr…

math.ST2024

Likelihood distortion and Bayesian local robustness

Antonio Di Noia, Fabrizio Ruggeri, Antonietta Mira

Robust Bayesian analysis has been mainly devoted to detecting and measuring robustness w.r.t. the prior distribution. Many contributions in the literature aim to define suitable cl…

stat.ML2024★ 1 cited

Scale adaptive and robust intrinsic dimension estimation via optimal neighbourhood identification

Antonio Di Noia, Iuri Macocco, Aldo Glielmo +2

The Intrinsic Dimension (ID) is a key concept in unsupervised learning and feature selection, as it is a lower bound to the number of variables which are necessary to describe a sy…

math.ST2024★ 1 cited

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…

stat.ME2023

Bayesian size-and-shape regression modelling

Antonio Di Noia, Gianluca Mastrantonio, Giovanna Jona Lasinio

Building on Dryden et al. (2021), this note presents the Bayesian estimation of a regression model for size-and-shape response variables with Gaussian landmarks. Our proposal fits…

math.ST2022★ 1 cited

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.ST2021★ 3 cited

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…

math.ST2021★ 5 cited

Goodness-of-fit test for count distributions with finite second moment

Antonio Di Noia, Lucio Barabesi, Marzia Marcheselli +2

A goodness-of-fit test for one-parameter count distributions with finite second moment is proposed. The test statistic is derived from the distance of a function of the proba…