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In probability theory, an empirical process is a stochastic process that describes the proportion of objects in a system in a given state.For a process in a discrete state space a population continuous time Markov chain or Markov population model is a process which counts the number of objects in a given state (without rescaling).In mean field theory, limit theorems (as the number of objects becomes large) are considered and generalise the central limit theorem for empirical measures. Applications of the theory of empirical processes arise in non-parametric statistics.

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rdf:type	Election
rdfs:label	Empirical process (en) Processus empirique (fr) 経験過程 (ja) Processo empírico (pt)
rdfs:comment	In probability theory, an empirical process is a stochastic process that describes the proportion of objects in a system in a given state.For a process in a discrete state space a population continuous time Markov chain or Markov population model is a process which counts the number of objects in a given state (without rescaling).In mean field theory, limit theorems (as the number of objects becomes large) are considered and generalise the central limit theorem for empirical measures. Applications of the theory of empirical processes arise in non-parametric statistics. (en) En probabilités, le processus empirique est un processus stochastique qui s'exprime en fonction de la proportion d'objets appartenant à un certain ensemble. Ce processus fait intervenir les déviations d'une statistique autour de sa moyenne et sera donc utile dans l'étude de la plupart d'entre elles. (fr) 経験過程（けいけんかてい、英: empirical process）は、経験測度の中心極限定理の一般化のひとつである。経験過程の理論は、ノンパラメトリック統計学などに応用される。 (ja) Em teoria das probabilidades, um processo empírico é um processo estocástico que descreve a proporção de objetos em um sistema em um dado estado. Para um processo em um espaço de estados discreto, uma cadeia de Markov populacional de tempo contínuo ou modelo populacional de Markov é um processo que conta o número de objetos em um dado estado (sem reescalonamento). Na teoria de campo médio, teoremas do limite (conforme o número de objetos se torna grande) são considerados e generalizam o teorema central do limite para medidas empíricas. Aplicações da teoria dos processos empíricos surgem na estatística não paramétrica. (pt)
dcterms:subject	Nonparametric statistics Empirical process
Wikipage page ID	3690433 (xsd:integer)
Wikipage revision ID	1050340569 (xsd:integer)
Link from a Wikipage to another Wikipage	Converges in distribution Almost surely Donsker's theorem Convergence of random variables Mean field theory Signed measure Empirical distribution function Gaussian process Empirical measure Khmaladze transformation Central limit theorem Cumulative distribution function Normal distribution Glivenko–Cantelli theorem Pointwise convergence Uniform convergence Probability theory Nonparametric statistics Law of large numbers Weak convergence of measures Iid Indicator function Brownian bridge Empirical process Non-parametric statistics Stochastic process Independent and identically-distributed random variables Glivenko–Cantelli class dbr:Donsker_classes
Link from a Wikipage to an external page	http://www.bios.unc.edu/~kosorok/current.pdf http://www.stat.yale.edu/~pollard/Books/Iowa
sameAs	Empirical process Empirical process Empirical process Empirical process Empirical process Empirical process Empirical process
dbp:wikiPageUsesTemplate	dbt:Cite_book dbt:Cite_journal dbt:For dbt:Reflist dbt:Stochastic_processes
has abstract	In probability theory, an empirical process is a stochastic process that describes the proportion of objects in a system in a given state.For a process in a discrete state space a population continuous time Markov chain or Markov population model is a process which counts the number of objects in a given state (without rescaling).In mean field theory, limit theorems (as the number of objects becomes large) are considered and generalise the central limit theorem for empirical measures. Applications of the theory of empirical processes arise in non-parametric statistics. (en) En probabilités, le processus empirique est un processus stochastique qui s'exprime en fonction de la proportion d'objets appartenant à un certain ensemble. Ce processus fait intervenir les déviations d'une statistique autour de sa moyenne et sera donc utile dans l'étude de la plupart d'entre elles. (fr) 経験過程（けいけんかてい、英: empirical process）は、経験測度の中心極限定理の一般化のひとつである。経験過程の理論は、ノンパラメトリック統計学などに応用される。 (ja) Em teoria das probabilidades, um processo empírico é um processo estocástico que descreve a proporção de objetos em um sistema em um dado estado. Para um processo em um espaço de estados discreto, uma cadeia de Markov populacional de tempo contínuo ou modelo populacional de Markov é um processo que conta o número de objetos em um dado estado (sem reescalonamento). Na teoria de campo médio, teoremas do limite (conforme o número de objetos se torna grande) são considerados e generalizam o teorema central do limite para medidas empíricas. Aplicações da teoria dos processos empíricos surgem na estatística não paramétrica. (pt)
gold:hypernym	Process
prov:wasDerivedFrom	wikipedia-en:Empirical_process?oldid=1050340569&ns=0
page length (characters) of wiki page	8351 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Empirical_process
is Link from a Wikipage to another Wikipage of	List of probability topics Convergence of random variables Empirical distribution function Convergence of Probability Measures Empirical measure Khmaladze transformation Action research Estate Khmaladze Dirichlet process Florentina Bunea Komlós–Major–Tusnády approximation Process Learnable function class Richard M. Dudley Empirical (disambiguation) Empirical Process Empirical procedure Empirical process theory Empirical processes FCLT Brownian bridge Catalog of articles in probability theory List of statistics articles Shattered set PCTMC Functional central limit theorem Markov population model Population continuous time Markov chain
is Wikipage redirect of	Empirical Process Empirical procedure Empirical process theory Empirical processes FCLT PCTMC Functional central limit theorem Markov population model

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