Sufficientness postulates for measure-valued Pólya urn sequences

Abstract In a recent paper, the authors studied the distribution properties of a class of exchangeable processes, called measure-valued Pólya sequences (MVPSs), which arise as the observation process in a generalized urn sampling scheme. Here we present several results in the form of ‘sufficientness’ postulates that characterize their predictive distributions. In particular, we show that exchangeable MVPSs are the unique exchangeable models whose predictive distributions are a mixture of the marginal distribution and the average of a probability kernel evaluated at past observations. When the latter coincides with the empirical measure, we recover a well-known result for the exchangeable model with a Dirichlet process prior. In addition, we provide a ‘pure’ sufficientness postulate for exchangeable MVPSs that does not assume a particular analytic form for the predictive distributions. Two other sufficientness postulates consider the case when the state space is finite.

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Publication Details

Journal
Journal of Applied Probability
Published
2025-03-28
DOI
https://doi.org/10.1017/jpr.2024.109
Primary Topic
Mathematical Dynamics and Fractals
Type
article
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article

Sufficientness postulates for measure-valued Pólya urn sequences

Mladen Savov, Hristo Sariev
Journal of Applied Probability
Mathematical Dynamics and Fractals
article

Sufficientness postulates for measure-valued Pólya urn sequences

Mladen Savov, Hristo Sariev
article en

Abstract

Abstract In a recent paper, the authors studied the distribution properties of a class of exchangeable processes, called measure-valued Pólya sequences (MVPSs), which arise as the observation process in a generalized urn sampling scheme. Here we present several results in the form of ‘sufficientness’ postulates that characterize their predictive distributions. In particular, we show that exchangeable MVPSs are the unique exchangeable models whose predictive distributions are a mixture of the marginal distribution and the average of a probability kernel evaluated at past observations. When the latter coincides with the empirical measure, we recover a well-known result for the exchangeable model with a Dirichlet process prior. In addition, we provide a ‘pure’ sufficientness postulate for exchangeable MVPSs that does not assume a particular analytic form for the predictive distributions. Two other sufficientness postulates consider the case when the state space is finite.

Journal of Applied ProbabilityVol. 62(3)
Bulgarian Academy of Sciences (BG)
Openalex Percentile: Top 90%
Mathematical Dynamics and Fractals
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