A user-friendly guide to Multivariate Calibration and Classification
by Tormod Næs, Tomas Isaksson, Tom Fearn, Tony Davies
Published: 2017
Edition: Second
Pages: xiii + 338
ISBN: 978-1-906715-25-0
DOI: 10.1255/978-1-906715-25-0
Inspiration and most of the material for A user-friendly guide to Multivariate Calibration and Classification came from the Chemometric Space columns that appeared in NIR news from 1991. There have been occasional guest columns over the years, but one or more of the authors of this book wrote most of the material. The authors are all very well known in the field and they bring a complementary range of experience and interests to this project.
A user-friendly guide to Multivariate Calibration and Classification provides a readable text, for non-mathematicians, as an introduction with little or moderate knowledge of chemometrics. It is aimed specifically at readers using chemometrics in the context of near infrared (NIR) spectroscopy. The techniques described are, however, much more widely applicable. Thus, although the columns were our starting point, our aim in rewriting and expanding them was to make this book a useful one for any chemometrics practitioner. Most of the examples still involve NIR spectroscopy, and some material that is specific to this application has been included, but we have tried to emphasise the generality of the approaches where ever possible.
The book has been designed in an attractive and easily read format, with many diagrams and the use of margin notes to highlight important features. This Second Edition includes Digital Object Identifiers (DOIs) for references where these are available, facilitating the finding of references online.
Table of Contents
Chapter 1: Basic problems and their solutions
Chapter 2: Univariate calibration and the need for multivariate methods
Chapter 3: Multicollinearity and the need for data compression
Chapter 4: Data compression by PCR and PLS
Chapter 5: Interpreting PCR and PLS solutions
Chapter 6: Data compression by variable selection
Chapter 7: Data compression by Fourier analysis and wavelets
Chapter 8: Non-linearity problems in calibration
Chapter 9: Scatter correction of spectroscopic data
Chapter 10: The idea behind and algorithm for locally weighted regression
Chapter 11: Other methods used to solve non-linearity problems
Chapter 12: Validation
Chapter 13: Outlier detection
Chapter 14: Selection of samples for calibration
Chapter 15: Monitoring calibration equations
Chapter 16: Standardisation of instruments
Chapter 17: Qualitative analysis/classification
Chapter 18: Abbreviations and symbols
Appendix A: Technical details
Appendix B: NIR spectroscopy
Appendix C: Proposed calibration and classification procedures