Robust functional principal component analysis for non-Gaussian longitudinal data

DOI10.1016/j.jmva.2021.104864zbMath1493.62376arXiv2102.00911OpenAlexW3208809677MaRDI QIDQ115416

Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang, Rou Zhong, Haocheng Li, Shishi Liu, Jing-Xiao Zhang

Publication date: May 2022

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2102.00911

zbMATH Keywords

functional principal component analysislocal polynomial smoothernon-Gaussianlongitudinal studyKendall's \(\tau\) function

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Functional data analysis (62R10)

Related Items (1)

KFPCA

Uses Software

• fda (R)
• sn

Cites Work

• A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
• Fast covariance estimation for sparse functional data
• An introduction to recent advances in high/infinite dimensional statistics
• From sparse to dense functional data and beyond
• Inference for functional data with applications
• Robust functional principal components: a projection-pursuit approach
• Uniform convergence rates for nonparametric regression and principal component analysis in functional/longitudinal data
• Optimal estimation of the mean function based on discretely sampled functional data: phase transition
• Robust principal component analysis for functional data. (With comments)
• A note on modeling sparse exponential-family functional response curves
• Recent advances in functional data analysis and high-dimensional statistics
• The spatial sign covariance operator: asymptotic results and applications
• Principal component analysis for functional data on Riemannian manifolds and spheres
• Independent component analysis for multivariate functional data
• Covariate adjusted functional principal components analysis for longitudinal data
• Functional single index models for longitudinal data
• Functional data analysis.
• Nonparametric functional data analysis. Theory and practice.
• Properties of principal component methods for functional and longitudinal data analysis
• Efficient semiparametric regression for longitudinal data with nonparametric covariance estimation
• Efficient Estimation of the Nonparametric Mean and Covariance Functions for Longitudinal and Sparse Functional Data
• Dispersion operators and resistant second-order functional data analysis
• Robust functional estimation using the median and spherical principal components
• Multivariate functional principal component analysis: A normalization approach
• Modelling Sparse Generalized Longitudinal Observations with Latent Gaussian Processes
• UNIFORM CONVERGENCE RATES FOR KERNEL ESTIMATION WITH DEPENDENT DATA
• Statistical Applications of the Multivariate Skew Normal Distribution
• MULTIVARIATE LOCAL POLYNOMIAL REGRESSION FOR TIME SERIES:UNIFORM STRONG CONSISTENCY AND RATES
• ECA: High-Dimensional Elliptical Component Analysis in Non-Gaussian Distributions
• Multivariate Functional Principal Component Analysis for Data Observed on Different (Dimensional) Domains
• Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
• S-Estimators for Functional Principal Component Analysis
• Regression Analysis of Sparse Asynchronous Longitudinal Data
• A pairwise interaction model for multivariate functional and longitudinal data
• Optimal Designs for Longitudinal and Functional Data
• Functional Data Analysis for Sparse Longitudinal Data
• A NEW MEASURE OF RANK CORRELATION
• Functional data analysis for density functions by transformation to a Hilbert space

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