Wasserstein distance error bounds for the multivariate normal approximation of the maximum likelihood estimator

DOI10.1214/21-EJS1920zbMath1482.60031arXiv2005.05208MaRDI QIDQ2074310

Andreas Anastasiou, Robert E. Gaunt

Publication date: 9 February 2022

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2005.05208

zbMATH Keywords

maximum likelihood estimationStein's methodnormal approximationWasserstein distancemultivariate normal approximation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Central limit and other weak theorems (60F05) Point estimation (62F10) Approximations to statistical distributions (nonasymptotic) (62E17)

Related Items (4)

Stein's method meets computational statistics: a review of some recent developments ⋮ Bounds in \(L^1\) Wasserstein distance on the normal approximation of general M-estimators ⋮ Estimation of smooth functionals in high-dimensional models: bootstrap chains and Gaussian approximation ⋮ New error bounds in multivariate normal approximations via exchangeable pairs with applications to Wishart matrices and fourth moment theorems

Uses Software

• DLMF
• gRc

Cites Work

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