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.
Di Noia, A., Marcheselli, M., Pisani, C., Pratelli, L. (2023). Censoring heavy-tail count distributions for parameter estimation with an application to stable distributions. STATISTICS & PROBABILITY LETTERS, 202, 1-5 [10.1016/j.spl.2023.109903].
Censoring heavy-tail count distributions for parameter estimation with an application to stable distributions
Marcheselli, Marzia;Pisani, Caterina
;
2023-01-01
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.
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Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/11365/1237994