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zbMATH Open
Article . 2024
Data sources: zbMATH Open
https://dx.doi.org/10.48550/ar...
Article . 2023
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Multidimensional Stein’s method for Gamma approximation

Multidimensional Stein's method for gamma approximation
Authors: Tudor, Ciprian A.; Zurcher, Jérémy;

Multidimensional Stein’s method for Gamma approximation

Abstract

Let F ($ν$) be the centered Gamma law with parameter $ν$ > 0 and let us denote by P Y the probability distribution of a random vector Y. We develop a multidimensional variant of the Stein's method for Gamma approximation that allows to obtain bounds for the second Wasserstein distance between the probability distribution of an arbitrary random vector (X, Y) in R x R n and the probability distribution F ($ν$) $\otimes$ P Y. In the case of random vectors with components in Wiener chaos, these bounds lead to some interesting criteria for the joint convergence of a sequence ((X n , Y n), n $\ge$ 1) to F ($ν$) $\otimes$ P Y , by assuming that (X n , n $\ge$ 1) converges in law, as n $\rightarrow$ $\infty$, to F ($ν$) and (Y n , n $\ge$ 1) converges in law, as n $\rightarrow$ $\infty$, to an arbitrary random vector Y. We illustrate our criteria by two concrete examples.

Keywords

multiple stochastic integrals, Stochastic integrals, Stochastic calculus of variations and the Malliavin calculus, Malliavin calculus, Probability (math.PR), FOS: Mathematics, Gaussian processes, Central limit and other weak theorems, Stein's method, asymptotic independence, Gamma approximation, Stein's equation, Mathematics - Probability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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