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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Non-integrable stable approximation by Stein's method [PDF]
, 2019 We develop Stein's method for $\alpha$-stable approximation with $\alpha\in(0,1]$, continuing the recent line of research by Xu \cite{lihu} and Chen, Nourdin and Xu \cite{C-N-X} in the case $\alpha\in(1,2).$ The main results include an intrinsic upper ...
Peng Chen +4 more
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Self-supervised MRI denoising: leveraging Stein’s unbiased risk estimator and spatially resolved noise maps [PDF]
Scientific Reports, 2023 Thermal noise caused by the imaged object is an intrinsic limitation in magnetic resonance imaging (MRI), resulting in an impaired clinical value of the acquisitions.
Laura Pfaff +8 more
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Automated Parameter Selection for Accelerated MRI Reconstruction via Low-Rank Modeling of Local k-Space Neighborhoods [PDF]
Zeitschrift für Medizinische Physik, 2023 Purpose: Image quality in accelerated MRI rests on careful selection of various reconstruction parameters. A common yet tedious and error-prone practice is to hand-tune each parameter to attain visually appealing reconstructions.
Efe Ilicak +2 more
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Performance Enhancement of INS and UWB Fusion Positioning Method Based on Two-Level Error Model [PDF]
Sensors, 2023 In GNSS-denied environments, especially when losing measurement sensor data, inertial navigation system (INS) accuracy is critical to the precise positioning of vehicles, and an accurate INS error compensation model is the most effective way to improve ...
Zhonghan Li +4 more
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Stein's method meets Malliavin calculus: a short survey with new estimates [PDF]
, 2009 We provide an overview of some recent techniques involving the Malliavin calculus of variations and the so-called ``Stein's method'' for the Gaussian approximations of probability distributions.
Ivan Nourdin, Giovanni Peccati
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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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Some recent advances for limit theorems [PDF]
ESAIM: Proceedings and Surveys, 2020 We present some recent developments for limit theorems in probability theory, illustrating the variety of this field of activity. The recent results we discuss range from Stein’s method, as well as for infinitely divisible distributions as applications ...
Arras Benjamin +4 more
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Approximation Results for Sums of Independent Random Variables
Revstat Statistical Journal, 2022 In this article, we consider Poisson and Poisson convoluted geometric approximation to the sums of n independent random variables under moment conditions. We use Stein’s method to derive the approximation results in total variation distance.
Pratima Eknath Kadu
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A non-uniform bound on binomial approximation to the beta binomial cumulative distribution function [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2019 This paper uses Stein’s method and the characterization of beta binomial random variable to determine a non-uniform bound for the distance between the beta binomial cumulative distribution function with parameters n N, 0 and 0 and the ...
Kanint Teerapabolarn, Khunakorn Sae-Jeng
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