Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal Polynomials

In this paper, we consider a quantitative fourth moment theorem for functions (random variables) defined on the Markov triple E,μ,Γ, where μ is a probability measure and Γ is the carré du champ operator. A new technique is developed to derive the fourth moment bound in a normal approximation on the...

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Main Authors: Yoon Tae Kim, Hyun Suk Park
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Journal of Function Spaces
Online Access:http://dx.doi.org/10.1155/2021/9408651
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author Yoon Tae Kim
Hyun Suk Park
author_facet Yoon Tae Kim
Hyun Suk Park
author_sort Yoon Tae Kim
collection DOAJ
description In this paper, we consider a quantitative fourth moment theorem for functions (random variables) defined on the Markov triple E,μ,Γ, where μ is a probability measure and Γ is the carré du champ operator. A new technique is developed to derive the fourth moment bound in a normal approximation on the random variable of a general Markov diffusion generator, not necessarily belonging to a fixed eigenspace, while previous works deal with only random variables to belong to a fixed eigenspace. As this technique will be applied to the works studied by Bourguin et al. (2019), we obtain the new result in the case where the chaos grade of an eigenfunction of Markov diffusion generator is greater than two. Also, we introduce the chaos grade of a new notion, called the lower chaos grade, to find a better estimate than the previous one.
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publishDate 2021-01-01
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series Journal of Function Spaces
spelling doaj-art-150864b436e640959ee54a87fd8218572025-02-03T01:25:08ZengWileyJournal of Function Spaces2314-88962314-88882021-01-01202110.1155/2021/94086519408651Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal PolynomialsYoon Tae Kim0Hyun Suk Park1Department of Statistics and Data Science Convergence Research Center, Hallym University, Chuncheon, Gangwon-Do 200-702, Republic of KoreaDepartment of Statistics and Data Science Convergence Research Center, Hallym University, Chuncheon, Gangwon-Do 200-702, Republic of KoreaIn this paper, we consider a quantitative fourth moment theorem for functions (random variables) defined on the Markov triple E,μ,Γ, where μ is a probability measure and Γ is the carré du champ operator. A new technique is developed to derive the fourth moment bound in a normal approximation on the random variable of a general Markov diffusion generator, not necessarily belonging to a fixed eigenspace, while previous works deal with only random variables to belong to a fixed eigenspace. As this technique will be applied to the works studied by Bourguin et al. (2019), we obtain the new result in the case where the chaos grade of an eigenfunction of Markov diffusion generator is greater than two. Also, we introduce the chaos grade of a new notion, called the lower chaos grade, to find a better estimate than the previous one.http://dx.doi.org/10.1155/2021/9408651
spellingShingle Yoon Tae Kim
Hyun Suk Park
Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal Polynomials
Journal of Function Spaces
title Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal Polynomials
title_full Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal Polynomials
title_fullStr Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal Polynomials
title_full_unstemmed Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal Polynomials
title_short Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal Polynomials
title_sort quantitative fourth moment theorem of functions on the markov triple and orthogonal polynomials
url http://dx.doi.org/10.1155/2021/9408651
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AT hyunsukpark quantitativefourthmomenttheoremoffunctionsonthemarkovtripleandorthogonalpolynomials