Computational aspects of algorithms for variable selection in the context of principal components

DOI10.1016/j.csda.2003.11.001zbMath1429.62216OpenAlexW2057367433MaRDI QIDQ82630

Manuel Minhoto, J.Orestes Cerdeira, Jorge Cadima, Manuel Minhoto, Jorge Cadima, Jorge Orestes Cerdeira

Publication date: September 2004

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

Full work available at URL: https://doi.org/10.1016/j.csda.2003.11.001

zbMATH Keywords

heuristicscombinatorial optimizationprincipal componentsvariable selectionprincipal variables

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (14)

Exact methods for variable selection in principal component analysis: guide functions and pre-selection ⋮ A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis ⋮ Statistical Sampling Strategies for Geometric Tolerance Inspection by CMM ⋮ An effective method of monitoring the large-scale traffic pattern based on RMT and PCA ⋮ Bayesian variable selection in generalized linear models using a combination of stochastic optimization methods ⋮ Principal component analysis: a review and recent developments ⋮ The max-out min-in problem: a tool for data analysis ⋮ Exact and approximate algorithms for variable selection in linear discriminant analysis ⋮ Unnamed Item ⋮ Applications of optimization heuristics to estimation and modelling problems ⋮ Transformation-based nonparametric estimation of multivariate densities ⋮ subselect ⋮ Variable selection in regression models using nonstandard optimisation of information criteria ⋮ Variable neighborhood search heuristics for selecting a subset of variables in principal component analysis

Uses Software

• R
• SoDA

Cites Work

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• Matrix correlation
• Principal component analysis.
• Discarding variables in a principal component analysis: algorithms for all-subsets comparisons
• Principal Variables
• Regressions by Leaps and Bounds
• Un critère de choix de variables en analyse en composantes principales fondé sur des modèles graphiques gaussiens particuliers
• Principal Component Analysis Based on a Subset of Variables: Variable Selection and Sensitivity Analysis
• Efficient variable screening for multivariate analysis

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