Some theoretical properties of Silverman's method for smoothed functional principal component analysis

DOI10.1016/j.jmva.2010.12.001zbMath1327.62223OpenAlexW1983935915WikidataQ42010163 ScholiaQ42010163MaRDI QIDQ632745

Xin Qi, Hongyu Zhao

Publication date: 25 March 2011

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

Full work available at URL: http://europepmc.org/articles/pmc3079282

zbMATH Keywords

convergence ratesfunctional central limit theoremasymptotic normalitysmoothing methodsfunctional PCAroughness penalty

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Functional limit theorems; invariance principles (60F17)

Related Items (4)

Some asymptotic theory for Silverman's smoothed functional principal components in an abstract Hilbert space ⋮ Unnamed Item ⋮ Interpretable functional principal component analysis ⋮ A modification of Silverman's method for smoothed functional principal components analysis

Uses Software

• fda (R)

Cites Work

• Asymptotic theory for the principal component analysis of a vector random function: Some applications to statistical inference
• Functional data analysis
• Functional linear model
• Smoothed functional principal components analysis by choice of norm
• Functional principal components analysis via penalized rank one approximation
• Nonparametric functional data analysis. Theory and practice.
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