Multivariate Prediction with Nonlinear Principal Components Analysis: Application
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DOI: 10.1007/s11135-005-3006-0
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References listed on IDEAS
- Blasius, Jörg & Thiessen, Victor, 2001. "Methodological Artifacts in Measures of Political Efficacy and Trust: A Multiple Correspondence Analysis," Political Analysis, Cambridge University Press, vol. 9(1), pages 1-20, January.
- John Gower & Jörg Blasius, 2005. "Multivariate Prediction with Nonlinear Principal Components Analysis: Theory," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(4), pages 359-372, August.
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Cited by:
- Blasius, Jörg & Eilers, Paul H.C. & Gower, John, 2009. "Better biplots," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3145-3158, June.
- Massimiliano Giacalone & Demetrio Panarello & Raffaele Mattera, 2018. "Multicollinearity in regression: an efficiency comparison between Lp-norm and least squares estimators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1831-1859, July.
- Bastiaan Bruinsma & Marlene Mußotter, 2023. "A Move Forward: Exploring National Identity Through Non-linear Principal Component Analysis in Germany," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 885-903, February.
- Bruno Ricca & Massimiliano Ferrara & Salvatore Loprevite, 2023. "Searching for an effective accounting-based score of firm performance: a comparative study between different synthesis techniques," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3575-3602, August.
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Keywords
Biplot; international comparison; large scale data analysis; national and regional identity; nonlinear principal components analysis; prediction;All these keywords.
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