Results 11 to 20 of about 6,587 (215)
Spin glasses and Stein's method [PDF]
Probability Theory and Related Fields, 2009 We introduce some applications of Stein's method in the high temperature analysis of spin glasses. Stein's method allows the direct analysis of the Gibbs measure without having to create a cavity.
Chatterjee, Sourav
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Discretized normal approximation by Stein's method
Bernoulli, 2014 We prove a general theorem to bound the total variation distance between the distribution of an integer valued random variable of interest and an appropriate discretized normal distribution.
Fang, Xiao
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Bernoulli, 2022 This paper proposes and studies a numerical method for approximation of posterior expectations based on interpolation with a Stein reproducing kernel. Finite-sample-size bounds on the approximation error are established for posterior distributions supported on a compact Riemannian manifold, and we relate these to a kernel Stein discrepancy (KSD ...
Barp A +3 more
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Stein’s method and Narayana numbers [PDF]
Statistics & Probability Letters, 2020 Narayana numbers appear in many places in combinatorics and probability, and it is known that they are asymptotically normal. Using Stein's method of exchangeable pairs, we provide an error of approximation in total variation to a symmetric binomial distribution of order~$n^{-1}$, which also implies a Kolmogorov bound of order~$n^{-1/2}$ for the normal
Jason Fulman, Adrian Röllin
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Electronic Journal of Probability, 2020 Applying an inductive technique for Stein and zero bias couplings yields Berry-Esseen theorems for normal approximation for two new examples. The conditions of the main results do not require that the couplings be bounded. Our two applications, one to the Erd s-R nyi, random graph with a fixed number of edges, and one to Jack measure on tableaux ...
Chen, L.H.Y., Goldstein, L., Röllin, A.
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Fundamentals of Stein’s method
Probability Surveys, 2011 This survey article discusses the main concepts and techniques of Stein's method for distributional approximation by the normal, Poisson, exponential, and geometric distributions, and also its relation to concentration inequalities. The material is presented at a level accessible to beginning graduate students studying probability with the main ...
Louis H. Y. Chen +2 more
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Stein's method of exchangeable pairs in multivariate functional approximations [PDF]
, 2021 In this paper we develop a framework for multivariate functional approximation by a suitable Gaussian process via an exchangeable pairs coupling that satisfies a suitable approximate linear regression property, thereby building on work by Barbour (1990 ...
Döbler, Christian +1 more
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Stein’s method on Wiener chaos [PDF]
Probability Theory and Related Fields, 2008 39 pages; Two sections added; To appear in ...
Nourdin, I., Peccati, G.
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Iperstoria, 2016 The article takes into account the way in which Gertrude Stein’s literary works have been interpreted by critics over the years. Following the writer’s own cue, scholars – starting with Stein’s long-time friend and admirer, Mable Dodge – have been ...
Enrico Frigeni
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Stein’s Method for Rough Paths [PDF]
Potential Analysis, 2019 The original Donsker theorem says that a standard random walk converges in distribution to a Brownian motion in the space of continuous functions. It has recently been extended to enriched random walks and enriched Brownian motion. We use the Stein-Dirichlet method to precise the rate of this convergence in the topology of fractional Sobolev spaces.
Coutin, Laure, Decreusefond, Laurent
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