Motivated by recent studies of big samples, this work aims at constructing a parametric model which is characterized by the following features: (i) a “local” reinforcement, i.e. a reinforcement mechanism mainly based on the last observations, (ii) a random persistent fluctuation of the predictive mean, and (iii) a long-term almost sure convergence of the empirical mean to a deterministic limit, together with a chi-squared goodness of fit result for the limit probabilities. This triple purpose has been achieved by the introduction of a new variant of the Eggenberger-Pólya urn, that we call the “Rescaled” Pólya urn. We provide a complete asymptotic characterization of this model, pointing out that, for a certain choice of the parameters, it has properties different from the ones typically exhibited from the other urn models in the literature. Therefore, beyond the possible statistical application, this work could be interesting for those who are concerned with stochastic processes with reinforcement.
The Rescaled Pólya Urn: local reinforcement and chi-squared goodness-of-fit test
Irene Crimaldi
2022-01-01
Abstract
Motivated by recent studies of big samples, this work aims at constructing a parametric model which is characterized by the following features: (i) a “local” reinforcement, i.e. a reinforcement mechanism mainly based on the last observations, (ii) a random persistent fluctuation of the predictive mean, and (iii) a long-term almost sure convergence of the empirical mean to a deterministic limit, together with a chi-squared goodness of fit result for the limit probabilities. This triple purpose has been achieved by the introduction of a new variant of the Eggenberger-Pólya urn, that we call the “Rescaled” Pólya urn. We provide a complete asymptotic characterization of this model, pointing out that, for a certain choice of the parameters, it has properties different from the ones typically exhibited from the other urn models in the literature. Therefore, beyond the possible statistical application, this work could be interesting for those who are concerned with stochastic processes with reinforcement.File | Dimensione | Formato | |
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