Three general approaches to Stein's method
2005; Linguagem: Inglês
10.1142/9789812567680_0004
ISSN1793-0758
Autores Tópico(s)Topological and Geometric Data Analysis
ResumoLecture Notes Series, Institute for Mathematical Sciences, National University of SingaporeAn Introduction to Stein's Method, pp. 183-221 (2005) No AccessThree general approaches to Stein's methodGesine ReinertGesine ReinertDepartment of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UKhttps://doi.org/10.1142/9789812567680_0004Cited by:31 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Abstract: Stein's method is in no way restricted to the particular settings discussed in the previous chapters: normal, Poisson and compound Poisson approximation for random variables, and Poisson point process approximation. This chapter is intended to illustrate that the method can be very generally exploited, and that one can set up and apply Stein's method in a wide variety of contexts. Three main approaches for achieving this are described: the generator method, density equations and coupling equations. These are applied to chi-squared approximation, to weak laws of large numbers in general spaces, including spaces of measures, and to discrete Gibbs distributions. The S-I-R epidemic model, which is discussed in some detail, serves to illustrate the extent of the possibilities. FiguresReferencesRelatedDetailsCited By 31Stein's Method Meets Computational Statistics: A Review of Some Recent DevelopmentsAndreas Anastasiou, Alessandro Barp, François-Xavier Briol, Bruno Ebner and Robert E. Gaunt et al.1 Feb 2023 | Statistical Science, Vol. 38, No. 1Quantitative two-scale stabilization on the Poisson spaceRaphaël Lachièze-Rey, Giovanni Peccati and Xiaochuan Yang1 Aug 2022 | The Annals of Applied Probability, Vol. 32, No. 4Approximations related to the sums of m-dependent random variablesAmit N. Kumar, Neelesh S. Upadhye and P. 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