Web7 de nov. de 2007 · Download PDF Abstract: In this paper we establish a multivariate exchangeable pairs approach within the framework of Stein's method to assess distributional distances to potentially singular multivariate normal distributions. By extending the statistics into a higher-dimensional space, we also propose an embedding method … WebIn this paper, we develop a different approach in Stein's method for discretized normal approximation. Our approach not only recovers the result of Chen and Leong [7], but also works for general integer valued random variables. We work under the framework of Stein coupling, a concept introduced by Chen and Röllin [8] under which normal ...
[1905.13615] Stein
WebStein’s method, normal approximation, local dependence, con-centration inequality, uniform Berry–Esseen bound, nonuniform Berry–Esseen bound, ran-dom field. This is an electronic reprint of the original article published by the Institute of Mathematical Statistics in The Annals of Probability, 2004, Vol. 32, No. 3A, 1985–2028. WebThis book provides an ideal introduction both to Stein's method and Malliavin calculus, from the standpoint of normal approximations on a Gaussian space. greetings from bury park chapter 3
Stein’s Method: Some Perspectives with Applications
WebThis paper presents Stein’s method from both a concrete and an abstract point ... G oldstein, L and G ordon, L. (1990) Poisson approximation and the Chen-Stein method. Statist. Sci. 5, 403–434. MathSciNet MATH Google Scholar A rratia, R., G ordon, L. and W aterman, M. S. (1990) The Erdös-Rényi law in distribution, for coin tossing and ... WebAbstract. Chapter 2 lays out the foundations of Stein’s method. First the Stein characterization for the normal is shown, and then bounds on the Stein equation, that will be required throughout the treatment, are derived. The multivariate Stein equation for the normal, and its solution by the generator method, is also presented. Web2. From characterization to approximation. A way to understand Stein’s method of normal approximation is to begin with Stein’s characterization of the normal distribution, which states that for a random variable W to have the standard normal distribution, it is necessaryand suffcient that (1) E{f′(W)−Wf(W)}=0 for f∈G, greetings from bury park characters