The most comprehensive, single-volume guide to conductingexperiments with mixtures
‘If one is involved, or heavily interested, in experiments onmixtures of ingredients, one must obtain this book. It is, as wasthe first edition, the definitive work.’
-Short Book Reviews (Publication of the International Statistical Institute)
‘The text contains many examples with worked solutions and with itsextensive coverage of the subject matter will prove invaluable tothose in the industrial and educational sectors whose work involvesthe design and analysis of mixture experiments.’
-Journal of the Royal Statistical Society
‘The author has done a great job in presenting the vitalinformation on experiments with mixtures in a lucid and readablestyle. . . . A very informative, interesting, and useful book on animportant statistical topic.’
-Zentralblatt fur Mathematik und Ihre Grenzgebiete
Experiments with Mixtures shows researchers and students how todesign and set up mixture experiments, then analyze the data anddraw inferences from the results. Virtually every technique thathas appeared in the literature of mixtures can be found here, andcomputing formulas for each method are provided with completelyworked examples. Almost all of the numerical examples are takenfrom real experiments. Coverage begins with Scheffe latticedesigns, introducing the use of independent variables, and endswith the most current methods. New material includes:
* Multiple response cases
* Residuals and least-squares estimates
* Categories of components: Mixtures of mixtures
* Fixed as well as variable values for the major componentproportions
* Leverage and the Hat Matrix
* Fitting a slack-variable model
* Estimating components of variances in a mixed model using ANOVAtable entries
* Clarification of blocking mates and choice of mates
* Optimizing several responses simultaneously
* Biplots for multiple responses
Table of Content
Preface to the Third Edition.
Preface to the Second Edition.
Introduction.
The Original Mixture Problem: Designs and Models for Exploring the Entire Simplex Factor Space.
The Use of Independent Variables.
Multiple Constraints on the Component Proportions.
The Analysis of Mixture Data.
Other Mixture Model Forms.
The Inclusion of Process Variables in Mixture Experiments.
Additional Topics.
Matrix Algebra, Least Squares, and the Analysis of Variance.
Data Sets from Mixture Experiments with Partial Solutions.
Bibliography and Index of Authors.
Answers to Selected Questions.
Appendix.
Index.
About the author
JOHN CORNELL is a professor in the Department of Statistics, University of Florida, Gainesville.
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