A general framework for multivariate functional principal component analysis of amplitude and phase variation

DOI10.1002/sta4.220MaRDI QIDQ6541495

Clara Happ, Alice-Agnes Gabriel, Sonja Greven, Fabian Scheipl

Publication date: 19 May 2024

Published in: Stat (Search for Journal in Brave)

zbMATH Keywords

registrationseismologyfunctional data analysisFréchet varianceBayes Hilbert spacetransformation of warping functions

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Simplicial principal component analysis for density functions in Bayes spaces
• Functional and shape data analysis
• \(k\)-mean alignment for curve clustering
• Functional data analysis of amplitude and phase variation
• Functional data analysis.
• Hilbert space of probability density functions based on Aitchison geometry
• Bayes Hilbert Spaces
• Combining Registration and Fitting for Functional Models
• Multivariate functional principal component analysis: A normalization approach
• Multivariate Functional Principal Component Analysis for Data Observed on Different (Dimensional) Domains
• An introduction to semiparametric function-on-scalar regression
• Functional data analysis for density functions by transformation to a Hilbert space

Related Items (4)

Comments on: ``Shape-based functional data analysis ⋮ A stochastic process representation for time warping functions ⋮ Latent deformation models for multivariate functional data and time-warping separability ⋮ Functional data analysis: an introduction and recent developments

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