Results 21 to 30 of about 7,698 (239)
Scandinavian Journal of StatisticsAbstractStein operators allow one to characterize probability distributions via differential operators. Based on these characterizations, we develop a new method of point estimation for marginal parameters of strictly stationary and ergodic processes, which we call Stein's Method of Moments (SMOM).
Bruno Ebner +4 more
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Bounds for the stop-loss distance of an independent random sum via Stein's method
AIMS MathematicsLet $ W = X_1+X_2+\cdots + X_N $ be a random sum and $ Z $ be the standard normal random variable. In this paper, we investigated uniform and non-uniform bounds of the stop-loss distance, which measures the difference between two random variables, $ W ...
Punyapat Kammoo +2 more
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Stein’s method for comparison of univariate distributions [PDF]
Probability Surveys, 2017 41 ...
Ley, Christophe +2 more
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Stein's method, Malliavin calculus, Dirichlet forms and the fourth moment theorem [PDF]
, 2014 The fourth moment theorem provides error bounds of the order $\sqrt{{\mathbb E}(F^4) - 3}$ in the central limit theorem for elements $F$ of Wiener chaos of any order such that ${\mathbb E}(F^2) = 1$.
Louis H. Y. Chen, Guillaume Poly
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Discretized normal approximation by Stein’s method
Bernoulli, 2014 Published in at http://dx.doi.org/10.3150/13-BEJ527 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)
Fang, Xiao
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Bounds for the chi-square approximation of Friedman's statistic by Stein's method [PDF]
Bernoulli, 2021 Friedman's chi-square test is a non-parametric statistical test for $r\geq2$ treatments across $n\ge1$ trials to assess the null hypothesis that there is no treatment effect.
Robert E. Gaunt, Gesine Reinert
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Gaussian random field approximation via Stein's method with applications to wide random neural networks [PDF]
Applied and Computational Harmonic Analysis, 2023 We derive upper bounds on the Wasserstein distance ($W_1$), with respect to $\sup$-norm, between any continuous $\mathbb{R}^d$ valued random field indexed by the $n$-sphere and the Gaussian, based on Stein's method.
K. Balasubramanian +3 more
semanticscholar +1 more source
Stein’s Method Meets Computational Statistics: A Review of Some Recent Developments [PDF]
Statistical Science, 2021 Stein's method compares probability distributions through the study of a class of linear operators called Stein operators. While mainly studied in probability and used to underpin theoretical statistics, Stein's method has led to significant advances in ...
Andreas Anastasiou +13 more
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The Prelimit Generator Comparison Approach of Stein’s Method [PDF]
Stochastic Systems, 2021 This paper uses the generator comparison approach of Stein’s method to analyze the gap between steady-state distributions of Markov chains and diffusion processes.
Anton Braverman
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Approximations of normal distribution by its q-generalizations [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2021 A concept of q-generalization of normal distribution arises in the context of statistical mechanics. In this article, we introduce a q-generalization of normal approximation.
Mongkhon Tuntapthai
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