Experiments with Mixtures: Designs, Models, and the Analysis of Mixture Data

The most comprehensive, single–volume guide to conducting experiments with mixtures
"If one is involved, or heavily interested, in experiments on mixtures of ingredients, one must obtain this book. It is, as was the first edition, the definitive work."
–Short Book Reviews (Publication of the International Statistical Institute)
"The text contains many examples with worked solutions and with its extensive coverage of the subject matter will prove invaluable to those in the industrial and educational sectors whose work involves the design and analysis of mixture experiments."
–Journal of the Royal Statistical Society
"The author has done a great job in presenting the vital information on experiments with mixtures in a lucid and readable style. . . . A very informative, interesting, and useful book on an important statistical topic."
–Zentralblatt fur Mathematik und Ihre Grenzgebiete
Experiments with Mixtures shows researchers and students how to design and set up mixture experiments, then analyze the data and draw inferences from the results. Virtually every technique that has appeared in the literature of mixtures can be found here, and computing formulas for each method are provided with completely worked examples. Almost all of the numerical examples are taken from real experiments. Coverage begins with Scheffe lattice designs, introducing the use of independent variables, and ends with the most current methods. New material includes:Multiple response casesResiduals and least–squares estimatesCategories of components: Mixtures of mixturesFixed as well as variable values for the major component proportionsLeverage and the Hat MatrixFitting a slack–variable modelEstimating components of variances in a mixed model using ANOVA table entriesClarification of blocking mates and choice of matesOptimizing se veral responses simultaneouslyBiplots for multiple responses

Spis treści:
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.

Nota biograficzna:
JOHN CORNELL is a professor in the Department of Statistics, University of Florida, Gainesville.

Okładka tylna:
The most comprehensive, single–volume guide to conducting experiments with mixtures
"If one is involved, or heavily interested, in experiments on mixtures of ingredients, one must obtain this book. It is, as was the first edition, the definitive work."
–Short Book Reviews (Publication of the International Statistical Institute)
"The text contains many examples with worked solutions and with its extensive coverage of the subject matter will prove invaluable to those in the industrial and educational sectors whose work involves the design and analysis of mixture experiments."
–Journal of the Royal Statistical Society
"The author has done a great job in presenting the vital information on experiments with mixtures in a lucid and readable style. . . . A very informative, interesting, and useful book on an important statistical topic."
–Zentralblatt fur Mathematik und Ihre Grenzgebiete
Experiments with Mixtures shows researchers and students how to design and set up mixture experiments, then analyze the data and draw inferences from the results. Virtually every technique that has appeared in the literature of mixtures can be found here, and computing formulas for each method are provided with completely worked examples. Almost all of the numerical examples are taken from real experiments. Coverage begins with Scheffe lattice designs, introducing the use of independent variables, and ends with the most current methods. New material includes:Multiple response casesResiduals and least–squares estimatesCategories of components: Mixtures of mixturesFixed as well as variable values for the major component proportionsLeverage and the Hat MatrixFitting a slack–variable modelEstimating components of variances in a mixed model using ANOVA table entriesClarification of blocking mates and choice of matesOptimizing several responses simultaneouslyBiplots for multiple responses