A Projection Algorithm for Regression with Collinearity

Author:

Filzmoser Peter,Croux Christophe

Publisher

Springer Berlin Heidelberg

Reference9 articles.

1. ARAúJO, M.C.U., SALDANHA, T.C.B., GALVãO, R.K.H., YONEYAMA, T., and CHAME, H.C. (2001): The Successive Projections Algorithm for Variable Selection in Spectroscopic Multicomponent Analysis. Chemometrics and Intelligent Laboratory Systems, 57, 65–73.

2. BASILEVSKY, A. (1994): Statistical Factor Analysis and Related Methods: Theory and Applications. Wiley & Sons, New York.

3. CROUX, C. and DEHON, C. (2001): Estimators of the Multiple Correlation Coefficient: Local Robustness and Confidence Intervals, to appear in Statistical Papers, http://www.econ.kuleuven.ac.be/ christophe.croux.

4. CROUX, C. and RUIZ-GAZEN, A. (1996): A Fast Algorithm for Robust Principal Components Based on Projection Pursuit. In: A. Prat (ed.): Computational Statistics. Physica-Verlag, Heidelberg, 211–216.

5. FILZMOSER, P. (2001): Robust Principal Compnent Regression. In: S. Aivazian, Yu. Kharin, and H. Rieder (Eds.): Computer Data Analysis and Modeling. Robust and Computer Intensive Methods. Belarusian State University, Minsk, 132–137.

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