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

Antonio Di Noia, Marzia Marcheselli, Caterina Pisani and Luca Pratelli

Statistics & Probability Letters, 2023, vol. 202, issue C

Abstract: 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 though a closed form of the probability mass function and/or finite moments do not exist.

Keywords: Asymptotic normality; Consistency; Data-driven; Probability generating function (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.spl.2023.109903

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