Comprehensive Chemometrics, 1st Edition

  • Steven Brown
  • Published By:
  • ISBN-10: 044452701X
  • ISBN-13: 9780444527011
  • Grade Level Range: College Freshman - College Senior
  • 2795 Pages | eBook
  • Original Copyright 2009 | Published/Released August 2011
  • This publication's content originally published in print form: 2009

  • Price:  Sign in for price



This book 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). It integrates coverage of chemical and biological methods, allowing readers to consider and test a range of techniques and consists of 2,200 pages and more than 90 review articles, making it the most comprehensive work of its kind. It also 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.

Table of Contents

Front Cover.
Half Title Page.
Other Frontmatter.
Title Page.
Copyright Page.
Contents of Volume 1.
Contributors to Volume 1.
Editors in Chief.
Contents of All Volumes.
Section Editors.
1: An Introduction to the Theory of Sampling: An Essential Part of Total Quality Management.
2: Quality of Analytical Measurements: Statistical Methods for Internal Validation.
3: Proficiency Testing in Analytical Chemistry.
4: Statistical Control of Measures and Processes.
5: Quality of Analytical Measurements: Univariate Regression.
6: Resampling and Testing in Regression Models with Environmetrical Applications.
7: Robust and Nonparametric Statistical Methods.
8: Bayesian Methodology in Statistics.
9: Experimental Design: Introduction.
10: Screening Strategies.
11: The Study of Experimental Factors.
12: Response Surface Methodology.
13: Experimental Design for Mixture Studies.
14: Nonclassical Experimental Designs.
15: Experimental Designs: Conclusions, Terminology, and Symbols.
16: Constrained and Unconstrained Optimization.
17: Sequential Optimization Methods.
18: Steepest Ascent, Steepest Descent, and Gradient Methods.
19: Multicriteria Decision-Making Methods.
20: Genetic Algorithms.