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

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

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  • Cadima, Jorge & Cerdeira, J. Orestes & Minhoto, Manuel, 2004. "Computational aspects of algorithms for variable selection in the context of principal components," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 225-236, September.
    • Handle: RePEc:eee:csdana:v:47:y:2004:i:2:p:225-236
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    References listed on IDEAS

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    1. António Pedro Duarte Silva, 2002. "Discarding Variables in a Principal Component Analysis: Algorithms for All-Subsets Comparisons," Computational Statistics, Springer, vol. 17(2), pages 251-271, July.
    2. W. J. Krzanowski, 1987. "Selection of Variables to Preserve Multivariate Data Structure, Using Principal Components," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(1), pages 22-33, March.
    3. J. Ramsay & Jos Berge & G. Styan, 1984. "Matrix correlation," Psychometrika, Springer;The Psychometric Society, vol. 49(3), pages 403-423, September.
    4. I. T. Jolliffe, 1973. "Discarding Variables in a Principal Component Analysis. Ii: Real Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 22(1), pages 21-31, March.
    5. Duarte Silva, António Pedro, 2001. "Efficient Variable Screening for Multivariate Analysis," Journal of Multivariate Analysis, Elsevier, vol. 76(1), pages 35-62, January.
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    Cited by:

    1. Brusco, Michael J. & Steinley, Douglas, 2011. "Exact and approximate algorithms for variable selection in linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 123-131, January.
    2. Kapetanios, George, 2007. "Variable selection in regression models using nonstandard optimisation of information criteria," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 4-15, September.
    3. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
    4. Michael Brusco & Renu Singh & Douglas Steinley, 2009. "Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 705-726, December.
    5. Rosa Guilherme & Alfredo Aires & Nuno Rodrigues & António M. Peres & José Alberto Pereira, 2020. "Phenolics and Antioxidant Activity of Green and Red Sweet Peppers from Organic and Conventional Agriculture: A Comparative Study," Agriculture, MDPI, vol. 10(12), pages 1-13, December.
    6. Fouskakis, D., 2012. "Bayesian variable selection in generalized linear models using a combination of stochastic optimization methods," European Journal of Operational Research, Elsevier, vol. 220(2), pages 414-422.
    7. Colosimo Bianca Maria & Moya Ester Gutierrez & Moroni Giovanni & Petrò Stefano, 2008. "Statistical Sampling Strategies for Geometric Tolerance Inspection by CMM," Stochastics and Quality Control, De Gruyter, vol. 23(1), pages 109-121, January.
    8. Pacheco, Joaquín & Casado, Silvia & Porras, Santiago, 2013. "Exact methods for variable selection in principal component analysis: Guide functions and pre-selection," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 95-111.
    9. Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.
    10. Chang, Meng-Shiuh & Wu, Ximing, 2015. "Transformation-based nonparametric estimation of multivariate densities," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 71-88.
    11. A. Pedro Duarte Silva, 2009. "Exact and heuristic algorithms for variable selection: Extended Leaps and Bounds," Working Papers de Economia (Economics Working Papers) 01, Católica Porto Business School, Universidade Católica Portuguesa.
    12. Brosnan, Kylie & Grün, Bettina & Dolnicar, Sara, 2018. "Identifying superfluous survey items," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 39-45.

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