About: Dirichlet process

Facets (new session)
Description
Metadata
Settings
- Rule:
- Inverse Functional Properties:
- "Same As":

About: Dirichlet process Goto Sponge NotDistinct Permalink

An Entity of Type : yago:StochasticProcess113561896, within Data Space : dbpedia.demo.openlinksw.com associated with source document(s)
QRcode icon

http://dbpedia.demo.openlinksw.com/c/HFe74D8gn

In probability theory, Dirichlet processes (after the distribution associated with Peter Gustav Lejeune Dirichlet) are a family of stochastic processes whose realizations are probability distributions. In other words, a Dirichlet process is a probability distribution whose range is itself a set of probability distributions. It is often used in Bayesian inference to describe the prior knowledge about the distribution of random variables—how likely it is that the random variables are distributed according to one or another particular distribution.

Attributes	Values
rdf:type	yago:WikicatNon-parametricBayesianMethods yago:WikicatStochasticProcesses yago:Ability105616246 yago:Abstraction100002137 yago:Cognition100023271 yago:Concept105835747 yago:Content105809192 yago:Hypothesis105888929 yago:Idea105833840 yago:Know-how105616786 yago:Method105660268 yago:Model105890249 yago:PsychologicalFeature100023100 yago:StochasticProcess113561896
rdfs:label	Procés de Dirichlet (ca) Dirichlet process (en) Processo de Dirichlet (pt)
rdfs:comment	In probability theory, Dirichlet processes (after the distribution associated with Peter Gustav Lejeune Dirichlet) are a family of stochastic processes whose realizations are probability distributions. In other words, a Dirichlet process is a probability distribution whose range is itself a set of probability distributions. It is often used in Bayesian inference to describe the prior knowledge about the distribution of random variables—how likely it is that the random variables are distributed according to one or another particular distribution. (en) Em teoria das probabilidades, os processos de Dirichlet, que recebem este nome em homenagem ao matemático alemão Johann Peter Gustav Lejeune Dirichlet, são uma família de processos estocásticos cujas observações são distribuições de probabilidade. Em outras palavras, um processo de Dirichlet é uma distribuição de probabilidade cujo intervalo é ele mesmo um conjunto de distribuições de probabilidade. É frequentemente usado em inferência bayesiana para descrever conhecimento a priori sobre a distribuição de variáveis aleatórias — qual a probabilidade de que as variáveis aleatórias sejam distribuídas de acordo com uma ou outra distribuição particular. (pt)
foaf:depiction
dct:subject	Nonparametric Bayesian statistics Stochastic processes
Wikipage page ID	8330403 (xsd:integer)
Wikipage revision ID	1115730164 (xsd:integer)
Link from a Wikipage to another Wikipage	Bayesian inference Probability distribution Natural language processing Pólya urn model Bernoulli distribution Almost surely Joint probability distribution Beta distribution Peter Gustav Lejeune Dirichlet Variance De Finetti's theorem Conditional independence Measurable set Pitman–Yor process Sign test Concentration parameter Conjugate prior Nonparametric statistics Statistical inference Bernstein–von Mises theorem Machine learning Nonparametric Bayesian statistics Chinese restaurant process Simplex Computer vision Empirical process Data mining Weak topology K-means clustering Expected value Normal distribution Partition of a set Dirichlet distribution Prior probability Probability theory Random variable Realization (probability) Wilcoxon signed-rank test Hierarchical Dirichlet process Stochastic processes Bioinformatics Data clustering Independence (probability theory) Independent and identically distributed random variables Indicator function Categorical distribution Real number Probability mass function Scale parameter Infinite mixture model Non-parametric statistics Imprecise Dirichlet process Unsupervised learning Exchangeable random variables Stochastic process Random variate Uncountable set Frequentist Gibbs sampler Discrete distribution Wilcoxon rank-sum test Continuous distribution Posterior distribution Stick-breaking process dbr:File:Chinese_Restaurant_Process_for_DP(0.5,H).webm dbr:File:Parameter_estimation_process_infinite_Gaussian_mixture_model.webm dbr:Sample_path
Link from a Wikipage to an external page	http://www.stats.bris.ac.uk/~peter/papers/GreenCDP.pdf http://www.cs.berkeley.edu/~jordan/nips-tutorial05.ps http://www.gatsby.ucl.ac.uk/~ywteh/research/npbayes/Teh2010a.pdf http://learning.eng.cam.ac.uk/zoubin/talks/uai05tutorial-b.pdf http://www.maths.bris.ac.uk/~maxvd/cribsheet.pdf http://ClusterAnalysis.org

Faceted Search & Find service v1.17_git147 as of Sep 06 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 08.03.3332 as of Dec 5 2024, on Linux (x86_64-generic-linux-glibc212), Single-Server Edition (378 GB total memory, 50 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software