Front of cover of the book

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