A stochastic process representation for time warping functions

DOI10.1016/J.CSDA.2024.107941zbMATH Open1543.62144MaRDI QIDQ6561274

Wei Wu, Yijia Ma, X. Y. Zhou

Publication date: 25 June 2024

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

Hilbert spacestochastic processisometric isomorphismfunctional boxplotpenalized function registrationtime warping functions

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Cites Work

• Title not available (Why is that?)
• Title not available (Why is that?)
• Generative models for functional data using phase and amplitude separation
• Functional and shape data analysis
• Analysis of proteomics data: Bayesian alignment of functions
• Analysis of spike train data: alignment and comparisons using the extended Fisher-Rao metric
• Analysis of spike train data: a multivariate mixed effects model for phase and amplitude
• Bayesian registration of functions and curves
• A geometric approach to pairwise Bayesian alignment of functional data using importance sampling
• Functional data analysis of amplitude and phase variation
• Multimodal Bayesian registration of noisy functions using Hamiltonian Monte Carlo
• Curve alignment by moments
• Hilbert space of probability density functions based on Aitchison geometry
• Bayes Hilbert spaces
• Curve Registration
• Self-Modelling Warping Functions
• Warped functional regression
• Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
• A general framework for multivariate functional principal component analysis of amplitude and phase variation

This page was built for publication: A stochastic process representation for time warping functions

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6561274)