Introduction to Multivariate Calibration: A Practical Approach

en Limba Engleză Hardback – 16 iul 2024

This book contains several new sections that provide even more in-depth knowledge on the topics. New content on the classical least-squares model, which shows its advantages and limitations in greater detail, was added. Additionally, the book contains a new section on the inverse least-squares model, which explains how it differs from the classical model and its applications in chemometrics. Furthermore, a new chapter on principal component analysis, which covers the concept in greater detail and its applications in chemometrics, is added. This book also includes several real-world examples to help you better understand the topic. Overall, this book provides the reader with even more comprehensive knowledge on chemometrics and multivariate calibration, making it an essential resource for students and professionals alike.

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Specificații

ISBN-13: 9783031641435
ISBN-10: 3031641434
Pagini: 302
Ilustrații: XX, 302 p. 185 illus., 178 illus. in color.
Dimensiuni: 155 x 235 mm
Ediția:Second Edition 2024
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland

Cuprins

1. Chemometrics and Multivariate Calibration.- 2. The Classical Least-Squares Model.- 3. The Inverse Least-Squares Model.- 4. Principal Component Analysis.- 5. Principal Component Regression.

Notă biografică

Prof. Dr. Alejandro César Olivieri obtained his B.Sc. in Industrial Chemistry from the Catholic Faculty of Chemistry and Engineering, Argentina, in 1982, and his Ph.D. from the Faculty of Biochemical and Pharmaceutical Sciences, University of Rosario, Argentina, in 1986. He works in the Department of Analytical Chemistry of the latter Faculty and is a fellow of the National Research Council of Argentina (CONICET). His primary research field is multivariate calibration, including first- and higher-order models, analytical figures of merit, and software development.

Textul de pe ultima copertă

This second edition builds upon the success of its predecessor with expanded and updated content throughout most chapters, accompanied by the addition of a new chapter on Non-linearities in Multivariate Calibration. This latest chapter explores advanced topics including Radial Basis Functions (RBF) and Feed-forward Networks (FFN), providing practical insights and real-world applications within the context of multivariate calibration. Readers will find intuitive explanations of mathematical and statistical concepts, supported by a wealth of figures and diagrams, alongside discussions on recent advancements in the field such as figures of merit, detection limits, and method comparison. With its emphasis on real applications and comprehensive updates, the second edition remains an invaluable resource for students, researchers, and practitioners navigating the complexities of multivariate analytical calibration.

Caracteristici

Simplifies complex concepts qualitatively, minimizing mathematical jargon Balances theory with practical exercises for comprehensive learning Showcases cutting-edge multivariate calibration advancements

Recenzii

Selected by Choice magazine as an Outstanding Academic Title for 2019
“Rich, concrete examples are lavishly illustrated, and ample references are provided. The text overall is challenging and rewarding for students and specialists alike.” (A. E. Viste, emeritus, Choice, Vol. 56 (10), June, 2019)

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