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Synopsis
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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About the Author
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.
From the Back Cover
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.
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 455 pp. Englisch. Seller Inventory # 9783031641435
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