Rating: 
(2 reviews)
Author: Edmund R. Malinowski
ISBN : 9780471134794
Buy New from $109.00
(2 reviews)Author: Edmund R. Malinowski
ISBN : 9780471134794
Buy New from $109.00
Factor analysis is a mathematical tool for examining a wide range of data sets, with applications especially important to the design of experiments (DOE), spectroscopy, chromatography, and chemometrics. Whereas the first two editions concentrated on standardizing the fundamentals of this emerging discipline, the Third Edition of Factor Analysis in Chemistry, the "bible" of factor analysis, proves a comprehensive handbook at a level that is consistent with the research and design of experiments today.
With the exception of updates, the introductory chapters remain unchanged. Chapter 6 has been edited to focus on evolutionary methods, including window factor analysis, transmutation, and DECRA. Selections on partial least squares and multimode analysis have been expanded and consolidated into two new chapters, 7 and 8. Some of the latest advances in a wide variety of fields, such as chromatography, NMR, biomedicine, environmental science, food, and fuels, are described in the applications chapters (chapters 9 through 12).
Other features of the book include:
- Provides history of the discipline as well as theory, philosophy, and applications
- Written for all readership levels: introductory, intermediate, and advanced
- Explains complicated concepts in simple language without sacrificing mathematical rigor
- Presents concepts and programs in a style that allows the user to develop programs in any computer language
- Demonstrates the utility of various factor analytical techniques for solving practical problems in chemistry and related sciences
- Showcases a unique presentation of partial least squares
- Hardcover: 432 pages
- Publisher: Wiley; 3 edition (March 7, 2002)
- Language: English
- ISBN-10: 0471134791
- ISBN-13: 978-0471134794
- Product Dimensions: 1 x 6.4 x 9 inches
- Shipping Weight: 1.6 pounds (View shipping rates and policies)
Factor Analysis in Chemistry
Preface.
Preface to the Second Edition.
Preface to the First Edition.
Historical Perspective of the Author.
Prologue.
Introduction.
Main Steps.
Mathematical Formulation of Target Factor Analysis.
Effects of Experimental Error on Target Factor Analysis.
Numerical Examples of Target Factor Analysis.
Evolutionary Methods.
Multimode Factor Analysis.
Partial Least-Squares Regression.
Component Analysis.
Nuclear Magnetic Resonance.
Chromatography.
Additional Applications.
Appendix A: Pseudoinverse.
Appendix B: Toolbox for Chemical Factor Analysis.
Appendix C: MATLAB Programs.
Bibliography.
Author Index.
Subject Index.
Preface to the Second Edition.
Preface to the First Edition.
Historical Perspective of the Author.
Prologue.
Introduction.
Main Steps.
Mathematical Formulation of Target Factor Analysis.
Effects of Experimental Error on Target Factor Analysis.
Numerical Examples of Target Factor Analysis.
Evolutionary Methods.
Multimode Factor Analysis.
Partial Least-Squares Regression.
Component Analysis.
Nuclear Magnetic Resonance.
Chromatography.
Additional Applications.
Appendix A: Pseudoinverse.
Appendix B: Toolbox for Chemical Factor Analysis.
Appendix C: MATLAB Programs.
Bibliography.
Author Index.
Subject Index.
The author does a good job with a tough topic. This is a fairly narrow niche of statistics that combines rigorous math and domain knowledge based heuristics. It is of interest to a small audience with very diverse background. Pure statisticians will probably be dissatisfied with the lack of rigor. People looking for a recipe to follow will probably find the book too theoretical.By craig
Given this challenge, the author acquits himself quite well. Very early on, he simply and clearly states the point of factor analysis. We get a good overview of the basic steps, and the options for tackling each one. The general statistical treatment is easy to skip for people who dont' need it, and seems fairly well done for people who do need it. We get some good examples and a detailed bibliography.
This is an excellent reference to the fascinating world of multivariate analysis.By David Schreck
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