Optimal bandwidth matrices in functional principal component analysis of density functions

DOI10.1080/00949655.2014.928293zbMath1457.62196OpenAlexW2065535036MaRDI QIDQ5220865

Smail Yousfi, Smail Adjabi, Rachid Boumaza, Djamil Aissani

Publication date: 27 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2014.928293

zbMATH Keywords

spectral theorynonparametric density estimationbandwidth matrixFPCA

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Density estimation (62G07) Estimation in multivariate analysis (62H12) Functional data analysis (62R10)

Uses Software

• fda (R)
• KernSmooth
• ks
• pyuvdata

Cites Work

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• Dimensionality reduction when data are density functions
• Asymptotic theory for the principal component analysis of a vector random function: Some applications to statistical inference
• Classifying densities using functional regression trees: applications in oceanology
• Convergence rates for unconstrained bandwidth matrix selectors in multivariate kernel density estimation
• Principal component analysis.
• Multivariate plug-in bandwidth selection
• Functional data analysis.
• Nonparametric functional data analysis. Theory and practice.
• Interpreting the Principal Component Analysis of Multivariate Density Functions
• Inference for Density Families Using Functional Principal Component Analysis
• Plug-in bandwidth matrices for bivariate kernel density estimation
• Cross-validation Bandwidth Matrices for Multivariate Kernel Density Estimation

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