Approximating by convolution of the normal and compound Poisson laws via Stein's method

DOI10.1007/s10986-018-9392-5zbMath1401.60031OpenAlexW2803607751WikidataQ114852327 ScholiaQ114852327MaRDI QIDQ1795401

Palaniappan Vellaisamy, Vydas Čekanavičius

Publication date: 16 October 2018

Published in: Lithuanian Mathematical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10986-018-9392-5

zbMATH Keywords

perturbationconvolutioncompound PoissonStein's methodnormal distribution

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05)

Cites Work

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• Approximating dependent rare events
• Fundamentals of Stein's method
• Stein's method for comparison of univariate distributions
• Stein's density approach and information inequalities
• On Stein's identity and its applications
• Asymptotic expansions in the Poisson limit theorem
• Compound Poisson approximation for nonnegative random variables via Stein's method
• Total variation asymptotics for sums of independent integer random variables
• Stein's method for conditional compound Poisson approximation
• On Stein operators for discrete approximations
• Characterizations of GIG laws: a survey
• Normal Approximation by Stein’s Method
• Poisson perturbations
• An Introduction to Stein's Method

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