Nonparametric bootstrap of sample means of positive-definite matrices with an application to diffusion-tensor-imaging data analysis

DOI10.1080/03610918.2015.1136413zbMath1377.62123OpenAlexW2398488382WikidataQ57428358 ScholiaQ57428358MaRDI QIDQ5373902

Armin Schwartzman, Leif Ellingson, David Groisser, Daniel E. Osborne, Victor Patrangenaru

Publication date: 27 October 2017

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc6709717

zbMATH Keywords

fast algorithmsnonparametric bootstrapdiffusion tensor imagingFréchet meanextrinsic meancenter of massintrinsic mean

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Image analysis in multivariate analysis (62H35) Nonparametric statistical resampling methods (62G09) Non-Euclidean differential geometry (53A35) Methods of local Riemannian geometry (53B21)

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Nonparametric two-sample tests on homogeneous Riemannian manifolds, Cholesky decompositions and diffusion tensor image analysis ⋮ Robustness of lognormal confidence regions for means of symmetric positive definite matrices when applied to mixtures of lognormal distributions

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