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Journal Articles Bayesian Analysis Year : 2019

Stochastic approximations to the Pitman-Yor process

Abstract

In this paper we consider approximations to the popular Pitman-Yor process obtained by truncating the stick-breaking representation. The truncation is determined by a random stopping rule that achieves an almost sure control on the approximation error in total variation distance. We derive the asymptotic distribution of the random truncation point as the approximation error goes to zero in terms of a polynomially tilted positive stable random variable. The practical usefulness and effectiveness of this theoretical result is demonstrated by devising a sampling algorithm to approximate functionals of the-version of the Pitman-Yor process.
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Dates and versions

hal-01950654 , version 1 (11-12-2018)

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Julyan Arbel, Pierpaolo de Blasi, Igor Prünster. Stochastic approximations to the Pitman-Yor process. Bayesian Analysis, 2019, 14 (3), pp.753-771. ⟨10.1214/18-BA1127⟩. ⟨hal-01950654⟩
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