On functional central limit theorems of Bayesian nonparametric priors

Luai Al Labadi; Ibrahim Abdelrazeq

doi:10.1007/s10260-016-0365-8

On functional central limit theorems of Bayesian nonparametric priors

Luai Al Labadi, Ibrahim Abdelrazeq

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

A general approach to derive the weak convergence, when centered and rescaled, of certain Bayesian nonparametric priors is proposed. This method may be applied to a wide range of processes including, for instance, nondecreasing nonnegative pure jump Lévy processes and normalized nondecreasing nonnegative pure jump Lévy processes with known finite dimensional distributions. Examples clarifying this approach involve the beta process in latent feature models and the Dirichlet process.

Original language	English
Pages (from-to)	215-229
Number of pages	15
Journal	Statistical Methods and Applications
Volume	26
Issue number	2
DOIs	https://doi.org/10.1007/s10260-016-0365-8
Publication status	Published - Jun 1 2017
Externally published	Yes

Keywords

Beta process
Dirichlet process
Lévy processes
Nonparametric Bayesian inference
Processes with independent increments
Quantile process
Weak convergence

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1007/s10260-016-0365-8

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AU - Abdelrazeq, Ibrahim

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AB - A general approach to derive the weak convergence, when centered and rescaled, of certain Bayesian nonparametric priors is proposed. This method may be applied to a wide range of processes including, for instance, nondecreasing nonnegative pure jump Lévy processes and normalized nondecreasing nonnegative pure jump Lévy processes with known finite dimensional distributions. Examples clarifying this approach involve the beta process in latent feature models and the Dirichlet process.

KW - Beta process

KW - Dirichlet process

KW - Lévy processes

KW - Nonparametric Bayesian inference

KW - Processes with independent increments

KW - Quantile process

KW - Weak convergence

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JF - Statistical Methods and Applications

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ER -

On functional central limit theorems of Bayesian nonparametric priors

Abstract

Keywords

ASJC Scopus subject areas

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