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Comprehensive Chemometrics

  • ID: 1758707
  • Book
  • 2896 Pages
  • Elsevier Science and Technology
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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
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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

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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).
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