Multivariate Stein Factors for a Class of Strongly Log-concave Distributions
classification
🧮 math.PR
keywords
steinboundsclassdistributionslog-concavemultivariatestronglyanalyzing
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We establish uniform bounds on the low-order derivatives of Stein equation solutions for a broad class of multivariate, strongly log-concave target distributions. These "Stein factor" bounds deliver control over Wasserstein and related smooth function distances and are well-suited to analyzing the computable Stein discrepancy measures of Gorham and Mackey. Our arguments of proof are probabilistic and feature the synchronous coupling of multiple overdamped Langevin diffusions.
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