Imprecise Dirichlet process
id:
imprecise-dirichlet-process-296-11141946
title:
Imprecise Dirichlet process
text:
In probability theory and statistics, the Dirichlet process (DP) is one of the most popular Bayesian nonparametric models. It was
introduced by Thomas Ferguson as a prior over probability distributions. A Dirichlet process D P is completely defined by its parameters: G 0 is an arbitrary distribution and s is a positive real number.
According to the Bayesian paradigm these parameters should be chosen based on the available prior information on the domain. The question is: how should we choose the
brand slug:
wiki
category slug:
encyclopedia
description:
Bayesian nonparametric model of probability distributions
original url:
https://en.wikipedia.org/wiki/Imprecise_Dirichlet_process
date created:
date modified:
2024-04-01T10:05:47Z
main entity:
{"identifier":"Q18208015","url":"https://www.wikidata.org/entity/Q18208015"}
image:
fields total:
13
integrity:
14