Introduction to Multivariate Calibration: A Practical Approach

Description

This book offers an introductory-level guide to the complex field of multivariate analytical calibration, with particular emphasis on real applications such as near infrared spectroscopy. It presents intuitive descriptions of mathematical and statistical concepts, illustrated with a wealth of figures and diagrams, and consistently highlights physicochemical interpretation rather than mathematical issues. In addition, it describes an easy-to-use and freely available graphical interface, together with a variety of appropriate examples and exercises. Lastly, it discusses recent advances in the field (figures of merit, detection limit, non-linear calibration, method comparison), together with modern literature references. Front Matter ....Pages i-xvii Chemometrics and Multivariate Calibration (Alejandro C. Olivieri)....Pages 1-17 The Classical Least-Squares Model (Alejandro C. Olivieri)....Pages 19-38 The Inverse Least-Squares Model (Alejandro C. Olivieri)....Pages 39-56 Principal Component Analysis (Alejandro C. Olivieri)....Pages 57-71 Principal Component Regression (Alejandro C. Olivieri)....Pages 73-86 The Optimum Number of Latent Variables (Alejandro C. Olivieri)....Pages 87-101 The Partial Least-Squares Model (Alejandro C. Olivieri)....Pages 103-121 Sample and Sensor Selection (Alejandro C. Olivieri)....Pages 123-137 Mathematical Pre-processing (Alejandro C. Olivieri)....Pages 139-158 Analytical Figures of Merit (Alejandro C. Olivieri)....Pages 159-177 MVC1: Software for Multivariate Calibration (Alejandro C. Olivieri)....Pages 179-205 Non-linearity and Artificial Neural Networks (Alejandro C. Olivieri)....Pages 207-226 Solutions to Exercises (Alejandro C. Olivieri)....Pages 227-236 Back Matter ....Pages 237-243