Description length and dimensionality reduction in functional data analysis

DOI10.1016/j.csda.2011.03.018zbMath1365.62225OpenAlexW2079422653MaRDI QIDQ2361186

D. S. Poskitt, Arivalzahan Sengarapillai

Publication date: 30 June 2017

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

Full work available at URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2009/wp13-09.pdf

zbMATH Keywords

bootstrapconsistencysignal-to-noise ratiovariance decompositionKarhunen-Loève expansiondimension determination

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Applications of statistics to physics (62P35)

Related Items (11)

Nonparametric operator-regularized covariance function estimation for functional data ⋮ Editorial: The third special issue on statistical signal extraction and filtering ⋮ Low-Rank Covariance Function Estimation for Multidimensional Functional Data ⋮ Model-based clustering for multivariate functional data ⋮ A survey of functional principal component analysis ⋮ Estimation of spatial-functional based-line logit model for multivariate longitudinal data ⋮ A block bootstrap for quasi-likelihood in sparse functional data ⋮ Long-Range Dependent Curve Time Series ⋮ Selecting the Number of Principal Components in Functional Data ⋮ Dependence measures for model selection in singular spectrum analysis ⋮ Resampling Techniques for Estimating the Distribution of Descriptive Statistics of Functional Data

Uses Software

• fda (R)
• rstiefel

Cites Work

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