Über die Autorin bzw. den Autor

Jose Andrade-Garda is based in the Department of Analytical Chemistry at the University of A Coru±a where he specializes in quality control and chemometrics. Within the field of chemometrics, his main interests are multivariate regression and pattern recognition methods. In the atomic spectrometry arena, he has applied formal optimization techniques to optimize analytical protocols and used multivariate regression tools to cope with spectral and chemical interferences in ETAAS.

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This is the first book for atomic spectroscopists to present the basic principles of experimental designs, optimization and multivariate regression. Multivariate regression is a valuable statistical method for handling complex problems (such as spectral and chemical interferences) which arise during atomic spectrometry. However, the technique is underused as most spectroscopists do not have time to study the often complex literature on the subject. This practical introduction uses conceptual explanations and worked examples to give readers a clear understanding of the technique. Mathematics is kept to a minimum but, when required, is kept at a basic level. Practical considerations, interpretations and troubleshooting are emphasized and literature surveys are included to guide the reader to further work. The same dataset is used for all chapters dealing with calibration to demonstrate the differences between the different methodologies. Readers will learn how to handle spectral and chemical interferences in atomic spectrometry in a new, more efficient and cost-effective way.

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Basic Chemometric Techniques in Atomic Spectroscopy

The Royal Society of Chemistry

Contents

List of Contributors, 
Chapter 1 An Overview of Atomic Spectrometric Techniques Alfredo Sanz-Medel, Rosario Pereiro and José Manuel Costa-Fernández, 
Chapter 2 Classical Linear Regression by the Least Squares Method José Manuel Andrade-Garda, Alatzne Carlosena-Zubieta, Rosa María Soto-Ferreiro, Javier Teran-Baamonde and Michael Thompson, 
Chapter 3 Implementing a Robust Methodology: Experimental Designs and Optimisation Xavier Tomàs-Morer, Lucinio González-Sabaté, Laura Fernández-Ruano and María Paz Gómez-Carracedo, 
Chapter 4 Ordinary Multiple Linear Regression and Principal Components Regression Joan Ferré-Baldrich and Ricard Boqué-Martí, 
Chapter 5 Partial Least-Squares Regression José Manuel Andrade-Garda, Alatzne Carlosena-Zubieta, Ricard Boqué-Martí and Joan Ferré-Baldrich, 
Chapter 6 Multivariate Regression using Artificial Neural Networks and Support Vector Machines José Manuel Andrade-Garda, Marcos Gestal-Pose, Francisco Abel Cedrón-Santaeufemia, Julián Dorado-de-la-Calle and María Paz Gómez-Carracedo, 
Subject Index,