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• Preface ; I BACKGROUND ; 1. Introduction ; 2. Some key ideas ; 3. Experimental strategies ; 4. The choice of a model ; 5. Models and least squares ; 6. Criteria for a good experiment ; 7. Standard designs ; 8. The analysis of experiments ; II THEORY AND APPLICATIONS ; 9. Optimum design theory ; 10. Criteria of optimality ; 11. D-optimum designs ; 12. Algorithms for the construction of exact D-optimum designs ; 13. Optimum experimental design with SAS ; 14. Experiments with both qualitative and quantitative factors ; 15. Blocking response surface designs ; 16. Mixture experiments ; 17. Nonlinear models ; 18. Bayesian optimum designs ; 19. Design augmentation ; 20. Model checking and designs for discriminating between models ; 21. Compound design criteria ; 22. Generalized linear models ; 23. Response transformation and structured variances ; 24. Time-dependent models with correlated observations ; 25. Further topics ; 26. Exercises ; Bibliography ; Author index ; Subject index

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• Preface ; I BACKGROUND ; 1. Introduction ; 2. Some key ideas ; 3. Experimental strategies ; 4. The choice of a model ; 5. Models and least squares ; 6. Criteria for a good experiment ; 7. Standard designs ; 8. The analysis of experiments ; II THEORY AND APPLICATIONS ; 9. Optimum design theory ; 10. Criteria of optimality ; 11. D-optimum designs ; 12. Algorithms for the construction of exact D-optimum designs ; 13. Optimum experimental design with SAS ; 14. Experiments with both qualitative and quantitative factors ; 15. Blocking response surface designs ; 16. Mixture experiments ; 17. Nonlinear models ; 18. Bayesian optimum designs ; 19. Design augmentation ; 20. Model checking and designs for discriminating between models ; 21. Compound design criteria ; 22. Generalized linear models ; 23. Response transformation and structured variances ; 24. Time-dependent models with correlated observations ; 25. Further topics ; 26. Exercises ; Bibliography ; Author index ; Subject index

Select Guide Rating

• Preface ; I BACKGROUND ; 1. Introduction ; 2. Some key ideas ; 3. Experimental strategies ; 4. The choice of a model ; 5. Models and least squares ; 6. Criteria for a good experiment ; 7. Standard designs ; 8. The analysis of experiments ; II THEORY AND APPLICATIONS ; 9. Optimum design theory ; 10. Criteria of optimality ; 11. D-optimum designs ; 12. Algorithms for the construction of exact D-optimum designs ; 13. Optimum experimental design with SAS ; 14. Experiments with both qualitative and quantitative factors ; 15. Blocking response surface designs ; 16. Mixture experiments ; 17. Nonlinear models ; 18. Bayesian optimum designs ; 19. Design augmentation ; 20. Model checking and designs for discriminating between models ; 21. Compound design criteria ; 22. Generalized linear models ; 23. Response transformation and structured variances ; 24. Time-dependent models with correlated observations ; 25. Further topics ; 26. Exercises ; Bibliography ; Author index ; Subject index