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Multiple imputation in principal component analysis

Author

Listed:
  • Julie Josse
  • Jérôme Pagès
  • François Husson
Abstract
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Suggested Citation

  • Julie Josse & Jérôme Pagès & François Husson, 2011. "Multiple imputation in principal component analysis," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(3), pages 231-246, October.
    • Handle: RePEc:spr:advdac:v:5:y:2011:i:3:p:231-246
    DOI: 10.1007/s11634-011-0086-7
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    References listed on IDEAS

    as
    1. Michael E. Tipping & Christopher M. Bishop, 1999. "Probabilistic Principal Component Analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 611-622.
    2. Dray, Stephane, 2008. "On the number of principal components: A test of dimensionality based on measurements of similarity between matrices," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2228-2237, January.
    3. Henk Kiers, 1997. "Weighted least squares fitting using ordinary least squares algorithms," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 251-266, June.
    4. Peres-Neto, Pedro R. & Jackson, Donald A. & Somers, Keith M., 2005. "How many principal components? stopping rules for determining the number of non-trivial axes revisited," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 974-997, June.
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    Citations

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    Cited by:

    1. Josse, Julie & Husson, François, 2012. "Selecting the number of components in principal component analysis using cross-validation approximations," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1869-1879.
    2. Nadia Solaro & Alessandro Barbiero & Giancarlo Manzi & Pier Alda Ferrari, 2017. "A sequential distance-based approach for imputing missing data: Forward Imputation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 395-414, June.
    3. Kaya, Orcun, 2022. "Determinants and consequences of SME insolvency risk during the pandemic," Economic Modelling, Elsevier, vol. 115(C).
    4. Federica Bandini & Enrico Supino, 2015. "Imprese sociali operanti in ambito sanitario: un?indagine esplorativa sui requisiti di aziendalit?," MECOSAN, FrancoAngeli Editore, vol. 2015(93), pages 115-136.
    5. Matthias Templ & Andreas Alfons & Peter Filzmoser, 2012. "Exploring incomplete data using visualization techniques," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(1), pages 29-47, April.
    6. Huiwen Wang & Shan Lu & Yide Liu, 2022. "Missing data imputation in PLS-SEM," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4777-4795, December.

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