Synopses & Reviews
The emphasis of this book is on understanding the principles and applications behind the main ideas in chemometrics, which can then be applied to a wide variety of problems in chemistry, chemical engineering and allied disciplines. The chapters cover experimental design, signal processing, pattern recognition, calibration and evolutionary data. The text is based around extensive work examples based primarily on the author's experience of more than a decade in chemometrics research and education both with university students and industrialists. In addition, the problems at the end of each chapter cover a wide range of applications to illustrate the broad applicability of these methods in different fields: these form an important part of the text, being a mixture of real case studies and simulations which are ideal for coursework or self study. For each of these 54 problems, the relevant sections of the text that provide further information are referenced. Appendices on matrix algebra, basic statistical concepts, common algorithms, Excel and MATLAB complete the book.
Readers may approach this book with different levels of knowledge and expectations. All calculations, graphs and answers to the worked examples and problems may be produced either in Excel or MATLAB or in most chemometrics packages according to the experience of the reader. Datasets and extensive worked solutions to the problems, together with downloadable Excel macros and a comprehensive set of MATLAB procedures corresponding to the methods presented in the text are available on www.SpectroscopyNow.com. The numerical answers have been very carefully validated and have been extensively tested in student seminars.
Synopsis
This book is aimed at the large number of people who need to use chemometrics but do not wish to understand complex mathematics, therefore it offers a comprehensive examination of the field of chemometrics without overwhelming the reader with complex mathematics.
* Includes five chapters that cover the basic principles of chemometrics analysis.
* Provides two chapters on the use of Excel and MATLAB for chemometrics analysis.
* Contains 70 worked problems so that readers can gain a practical understanding of the use of chemometrics.
Synopsis
This book is aimed at the large number of people who need to use chemometrics but do not wish to understand complex mathematics, therefore it offers a comprehensive examination of the field of chemometrics without overwhelming the reader with complex mathematics.
x Includes five chapters that cover the basic principles of chemometrics analysis.
x Provides two chapters on the use of Excel and MATLAB for chemometrics analysis.
x Contains 70 worked problems so that readers can gain a practical understanding of the use of chemometrics.
Synopsis
"Statisticians, chemical engineers, and computing scientists will find this book valuable and useful." (
Journal of Statistical Computation and Simulation, November 2005)
"In short, this is the best book that I have seen covering the entire field of modern chemometrics both for the academic and industrial user...I highly recommend it." (Technometrics, Vol. 46, No. 1, February 2004)
"...a useful introductory overview of a wide range of chemometric techniques..." (Organic Process Research & Development)
"...a pleasure to read this clear description of such a broad and complex area...worth its price..." (Zeitschrift fur Physikalische Chemie, Vol 218(2), 2004)
"...good job of explaining the nuts and bolts...recommend this book to anyone who wants to spend the time learning..." (Canadian Society of Forensic Science Journal, Vol 37(2), June 2004)
""...offers a comprehensive, practice-orientated examination of the field without overwhelming the reader with complex mathematics." (Metrohmm Information, Vol.33, No.3, 2004)
Table of Contents
Preface.
Supplementary Information.
Acknowledgements.
1. INTRODUCTION.
Points of View.
Software and Calculations.
Further Reading.
References.
2. EXPERIMENTAL DESIGN.
Introduction.
Basic Principles.
Factorial Designs.
Central Composite or Response Surface Designs.
Mixture Designs.
Simplex Optimisation.
Problems.
3. SIGNAL PROCESSING.
Sequential Signals in Chemistry.
Basics.
Linear Filters.
Correlograms and Time Series Analysis.
Fourier Transform Techniques.
Topical Methods.
Problems.
4. PATTERN RECOGNITION.
Introduction.
The Concept and Need for Principal Components Analysis.
Principal Components Analysis: the Method.
Unsupervised Pattern Recognition: Cluster Analysis.
Supervised Pattern Recognition.
Multiway Pattern Recognition.
Problems.
5. CALIBRATION.
Introduction.
Univariate Calibration.
Multiple Linear Regression.
Principal Components Regression.
Partial Least Squares.
Model Validation.
Problems.
6. EVOLUTIONARY SIGNALS.
Introduction.
Exploratory Data Analysis and Preprocessing.
Determining Composition.
Resolution.
Problems.
Appendices
A.1 Vectors and Matrices.
A.2 Algorithms.
A.3 Basic Statistical Concepts.
A.4 Excel for Chemometrics.
A.5 Matlab for Chemometrics.
Index