- From Mardia, Kent and Bibby. Multivariate Analysis (1979), Academic Press:
Chapter 1: Until section 1.7.3.
Chapter 2: 2.1, 2.2.1, 2.2.2. 2.5.1, 2.5.2, 2.5.3. Theorem 2.8.1 and Theorem 2.8.2.
Chapter 3: 3.1.1, Theorem 3.1.1, Theorem 3.2.1, Theorem 3.3.1, 3.4.1 (only page 66), Theorem 3.4.4c, 3.5 (only introduction, Corollary 3.5.2.1 plus use of the formula), 3.6.1.
Chapter 4: 4.2.2.1. (Until Theorem 4.2.1)
Chapter 6: 6.1, 6.2 (Until Theorem 6.2.3), 6.5 (Until section 6.5.4), 6.6 (Until section 6.6.3).
Chapter 8: 8.1, 8.2 (except section 8.2.4), Theorem 8.3.1,
Chapter 11: 11.1, 11.2.1, 11.2.2, 11.3.1, 11.5, 11.6.2, 11.6.3.
Chapter 12: Section 12.5.6 only.
Chapter 13: 13.1.1, 13.3.
Appendix: Theorem A.6.4, Theorem A.6.5, A.10.3, A.10.4.
- Main ideas and material covered in the lectures and exercises.
- Powerpoint presentations about PCA, PCR og PLS. Theory plus examples, on the web site.
- Næs, T. and Martens, H. (1988). Principal component regression in NIR analysis: Viewpoints, background details and selection of components. Journal of Chemometrics, 2, 155-167.
- Næs, T. and Isaksson, T. (1991). Multicollinearity and the need for data reduction. NIR news, 2, 6, 10-11.
- Næs, T. and Isaksson, T. (1991). Fitting, prediction testing, cross-validation or leverage correction. NIR news, 2, 5, 10-11.
- Næs, T. and Isaksson, T. (1992). The importance of outlier detection in NIR spectroscopy. NIR news, 3, 4, 12-13.
- Næs, T. and Isaksson, T. (1992). How can outliers be detected in NIR spectroscopy? NIR news, 3, 5, 8-9.
- Isaksson, T. and Næs, T. Principal component analysis.- a method for interpreting multivariate data. Distributed at lecture. (in Norwegian)
- Powerpoint presentation about classification. On the web-site.