Although widely used in science and technology for experimental data generating, modeling, and optimization, the response surface methodology (RSM) has many limitations. Showing how robust response surface methodology (RRSM) can overcome these limitations, Robust Response Surfaces, Regression, and Positive Data Analyses presents RRS designs, along with the relevant regression and positive data analysis techniques. It explains how to use RRSM in experimental designs and regression analysis.
The book addresses problems of RRS designs, such as rotatability, slope-rotatability, weak rotatability, and optimality. It describes methods for estimating model parameters as well as positive data analysis techniques. The author illustrates the concepts and methods with real examples of lifetime responses, resistivity, replicated measures, and more.
The range of topics and applications gives the book broad appeal both to theoreticians and practicing professionals. The book helps quality engineers, scientists in any area, medical practitioners, demographers, economists, and statisticians understand the theory and applications of RRSM. It can also be used in a second course on the design of experiments.
Preface
Chapter 1 : Introduction
Chapter 2 : Robust First-Order Designs
Chapter 3 : Robust Second-Order Designs
Chapter 4 : Lifetime Improvement Robust First-Order Designs
Chapter 5 : Lifetime Improvement Robust Second-Order Designs
Chapter 6 : Weakly Robust Rotatable Designs
Chapter 7 : Robust Second-Order Slope-Rotatability
Chapter 8 : Robust Second-Order Slope-Rotatability Over All Directions
Chapter 9 : Robust Second-Order Slope-Rotatable Designs with Maximum Directional Variance and D-Optimal Slope
Chapter 10 : Weakly Robust Second-Order Slope-Rotatable Designs
Chapter 11 : Regression Analysis for Correlated Observations
Chapter 12 : Applications of Correlated Regression Analyses
Chapter 13 : Positive Data Analyses
Chapter 14 : Applications of Log-Normal and Gamma Models
Index
