Identifying the informational/signal dimension in principal component analysis

DOI10.3390/math6110269zbMath1407.62215OpenAlexW2901366994WikidataQ128906089 ScholiaQ128906089MaRDI QIDQ1634747

Valério D. Pillar, Sergio Camiz

Publication date: 18 December 2018

Published in: Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3390/math6110269

zbMATH Keywords

bootstrap methodprincipal component analysisstopping rulessimulated datarules comparison

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Stopping times; optimal stopping problems; gambling theory (60G40)

Related Items (1)

Exploratory Classification of Time-Series

Uses Software

• sedaR
• Canoco
• bootstrap

Cites Work

• Selection of components in principal component analysis: A comparison of methods
• How many principal components? Stopping rules for determining the number of non-trivial axes revisited
• On the number of principal components: a test of dimensionality based on measurements of similarity between matrices
• Testing the significance of the \textit{RV} coefficient
• Bootstrap methods: another look at the jackknife
• Principal component analysis.
• Some necessary conditions for common-factor analysis
• Choosing Principal Components: A New Graphical Method Based on Bayesian Model Selection
• Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models
• A Monte Carlo examination of the broken-stick distribution to identify components to retain in principal component analysis
• Asymptotic Theory for Principal Component Analysis
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