The Annals of Probability

Tailfree and Neutral Random Probabilities and Their Posterior Distributions

Kjell Doksum

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Abstract

The random distribution function $F$ and its law is said to be neutral to the right if $F(t_1), \lbrack F(t_2) - F(t_1) \rbrack/\lbrack 1 - F(t_1)\rbrack, \cdots, \lbrack F(t_k) - F(t_{k-1}) \rbrack/\lbrack 1 - F(t_{k-1}) \rbrack$ are independent whenever $t_1 < \cdots < t_k$. The posterior distribution of a random distribution function neutral to the right is shown to be neutral to the right. Characterizations of these random distribution functions and connections between neutrality to the right and general concepts of neutrality and tailfreeness (tailfreedom) are given.

Article information

Source
Ann. Probab., Volume 2, Number 2 (1974), 183-201.

Dates
First available in Project Euclid: 19 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aop/1176996703

Digital Object Identifier
doi:10.1214/aop/1176996703

Mathematical Reviews number (MathSciNet)
MR373081

Zentralblatt MATH identifier
0279.60097

JSTOR
links.jstor.org

Subjects
Primary: 60K99: None of the above, but in this section
Secondary: 62C10: Bayesian problems; characterization of Bayes procedures 62G99: None of the above, but in this section

Keywords
Random probabilities posterior distributions processes Dirichlet process posterior mean of a process Bayes estimates tailfree neutral

Citation

Doksum, Kjell. Tailfree and Neutral Random Probabilities and Their Posterior Distributions. Ann. Probab. 2 (1974), no. 2, 183--201. doi:10.1214/aop/1176996703. https://projecteuclid.org/euclid.aop/1176996703


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