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This paper provides a general framework for Stein's density method for multivariate continuous distributions.
An optimal Poincaré inequality for convex domains
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A class of bivariate distributions including the bivariate logistic
M. M. Ali, N. Mikhail, and M. S. Haq · 1978
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Estimation of the mean of a multivariate normal distribution
C. M. Stein · 1981
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On Stein’s method for infinitely divisible laws with finite first moment
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On Stein’s method for multivariate self-decomposable laws with finite first moment
B. Arras and C. Houdré · 2019
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Existence of Stein kernels under a spectral gap, and discrepancy bound
T. A. Courtade, M. Fathi, and A. Pananjady · 2019
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Stein kernels and moment maps
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Weighted Poincaré inequalities, concentration inequalities and tail bounds related to the behavior of the Stein kernel in dimension one
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Testing normality via a distributional fixed point property in the stein characterization
S. Betsch and B. Ebner · 2020
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Stein’s method for normal approximation in Wasserstein distances with application to the multivariate Central Limit Theorem
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First-order covariance inequalities via Stein’s method
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Multivariate goodness-of-Fit tests based on Wasserstein distance
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Relaxing the Gaussian assumption in shrinkage and SURE in high dimension
M. Fathi, L. Goldstein, G. Reinert and A. Saumard · 2022
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