Comprehensive Chemometrics: Chemical and Biochemical Data Analysis

Erscheinungsjahr 2009
ISBN: 978-0-444-52702-8
Verlag: ELSEVIER SCIENCE PUB CO

Buch, Englisch, 2896 Seiten, Format (B × H): 222 mm x 286 mm

Designed to serve as the first point of reference on the subject, Comprehensive Chemometrics presents an integrated summary of the present state of chemical and biochemical data analysis and manipulation. The work covers all major areas ranging from statistics to data acquisition, analysis, and applications.

This major reference work provides broad-ranging, validated summaries of the major topics in chemometrics-with chapter introductions and advanced reviews for each area. The level of material is appropriate for graduate students as well as active researchers seeking a ready reference on obtaining and analyzing scientific data.



- Features the contributions of leading experts from 21 countries, under the guidance of the Editors-in-Chief and a team of specialist Section Editors: L. Buydens; D. Coomans; P. Van Espen; A. De Juan; J.H. Kalivas; B.K. Lavine; R. Leardi; R. Phan-Tan-Luu; L.A. Sarabia; and J. Trygg
- Examines the merits and limitations of each technique through practical examples and extensive visuals: 368 tables and more than 1,300 illustrations (750 in full color)
- Integrates coverage of chemical and biological methods, allowing readers to consider and test a range of techniques
- Consists of 2,200 pages and more than 90 review articles, making it the most comprehensive work of its kind
- Offers print and online purchase options, the latter of which delivers flexibility, accessibility, and usability through the search tools and other productivity-enhancing features of ScienceDirect

Zielgruppe

Graduate scientists and practitioners working on the analysis and manipulation of chemical and biological data.

Autoren/Hrsg.

Brown, Steven

Brown, Steven D.

Weitere Mitwirkende

Walczak, Beata

Fachgebiete

• Naturwissenschaften Chemie Organische Chemie Biochemie
• Naturwissenschaften Chemie Chemie Allgemein Chemometrik, Chemoinformatik
• Naturwissenschaften Chemie Analytische Chemie

Inhaltsverzeichnis

Statistics Experimental Design Optimization Data preprocessing Linear soft-modeling Unsupervised Data Mining Linear Regression Modeling Non-linear Regression Classification Feature Selection Multivariate Robust Techniques Applications

Über Autor(innen)

Brown, Steven D.
Expertise in chemical data analysis, including signal processing and detection, background removal, and transfer of multivariate calibrations. Data mining and knowledge discovery of chemical relationships involving multivariate data, including development of novel classifiers and hierarchical classification methods. Fusion of chemical sensor data for classification and calibration. Former EIC of Editor-in-Chief, Journal of Chemometrics (1994-2007), Editorial Board Member of Nature Scientific Reports and Journal of Chemometrics, Winner of Best Applied Chemometrics Paper 2015 (Wiley, Kowalski Award).

Walczak, Beata
Professor Walczak has been working in the Institute of Chemistry, University of Silesia since 1979, where now she is the head of the Department of Analytical Chemistry. She has authored and co-authored around 165 scientific papers, 400 conference papers, and delivered many invited lectures at international chemistry meetings. Currently she acts as Editor of the journal Chemometrics and Intelligent Laboratory Systems and of 'Data Handling in Chemistry and Technology' (the Elsevier book series), and as a member of the editorial boards of Talanta, Analytical Letters, J. Chemometrics, and Acta Chromatographica. She has been involved in chemometrics since the early 1990s and her main scientific interests are in all aspects of data exploration and modelling (dealing with missing and censored data, dealing with outliers, data representatively, enhancement of instrumental signals, signal warping, data compression, linear and non-linear projections, development of modeling approaches, feature selection techniques etc.). She has an h-index of 40.