Regression for non-Euclidean data using distance matrices

DOI10.1080/02664763.2014.909794OpenAlexW2010096196MaRDI QIDQ5130534

Julian J. Faraway

Publication date: 28 October 2020

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

Full work available at URL: https://arxiv.org/abs/1303.3750

zbMATH Keywords

correlation matrixfunctional data analysismixed datamultidimensional scaling

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (5)

Global and local distance-based generalized linear models ⋮ Intrinsic Riemannian functional data analysis for sparse longitudinal observations ⋮ Fréchet single index models for object response regression ⋮ Fréchet regression for random objects with Euclidean predictors ⋮ Total variation regularized Fréchet regression for metric-space valued data

Uses Software

• pls
• fda (R)
• shapes

Cites Work

• Computing the nearest correlation matrix--a problem from finance
• Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging
• Object oriented data analysis: sets of trees
• Functional data analysis.
• Bayesian analysis of covariance matrices and dynamic models for longitudinal data
• Adding a point to vector diagrams in multivariate analysis
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