Response Surfaces, Mixtures, and Ridge Analyses
Response Surfaces, Mixtures, and Ridge Analyses

Author: George E. P. Box

Publisher: John Wiley & Sons

Published: 2007-01-22

Total Pages: 880

ISBN-13: 047007275X

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The authority on building empirical models and the fitting of such surfaces to data—completely updated and revised Revising and updating a volume that represents the essential source on building empirical models, George Box and Norman Draper—renowned authorities in this field—continue to set the standard with the Second Edition of Response Surfaces, Mixtures, and Ridge Analyses, providing timely new techniques, new exercises, and expanded material. A comprehensive introduction to building empirical models, this book presents the general philosophy and computational details of a number of important topics, including factorial designs at two levels; fitting first and second-order models; adequacy of estimation and the use of transformation; and occurrence and elucidation of ridge systems. Substantially rewritten, the Second Edition reflects the emergence of ridge analysis of second-order response surfaces as a very practical tool that can be easily applied in a variety of circumstances. This unique, fully developed coverage of ridge analysis—a technique for exploring quadratic response surfaces including surfaces in the space of mixture ingredients and/or subject to linear restrictions—includes MINITAB® routines for performing the calculations for any number of dimensions. Many additional figures are included in the new edition, and new exercises (many based on data from published papers) offer insight into the methods used. The exercises and their solutions provide a variety of supplementary examples of response surface use, forming an extremely important component of the text. Response Surfaces, Mixtures, and Ridge Analyses, Second Edition presents material in a logical and understandable arrangement and includes six new chapters covering an up-to-date presentation of standard ridge analysis (without restrictions); design and analysis of mixtures experiments; ridge analysis methods when there are linear restrictions in the experimental space including the mixtures experiments case, with or without further linear restrictions; and canonical reduction of second-order response surfaces in the foregoing general case. Additional features in the new edition include: New exercises with worked answers added throughout An extensive revision of Chapter 5: Blocking and Fractionating 2k Designs Additional discussion on the projection of two-level designs into lower dimensional spaces This is an ideal reference for researchers as well as a primary text for Response Surface Methodology graduate-level courses and a supplementary text for Design of Experiments courses at the upper-undergraduate and beginning-graduate levels.

Response Surface Methodology
Response Surface Methodology

Author: Raymond H. Myers

Publisher: John Wiley & Sons

Published: 2016-01-04

Total Pages: 854

ISBN-13: 1118916034

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Praise for the Third Edition: “This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern applications of RSM.” - Zentralblatt Math Featuring a substantial revision, the Fourth Edition of Response Surface Methodology: Process and Product Optimization Using Designed Experiments presents updated coverage on the underlying theory and applications of response surface methodology (RSM). Providing the assumptions and conditions necessary to successfully apply RSM in modern applications, the new edition covers classical and modern response surface designs in order to present a clear connection between the designs and analyses in RSM. With multiple revised sections with new topics and expanded coverage, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition includes: Many updates on topics such as optimal designs, optimization techniques, robust parameter design, methods for design evaluation, computer-generated designs, multiple response optimization, and non-normal responses Additional coverage on topics such as experiments with computer models, definitive screening designs, and data measured with error Expanded integration of examples and experiments, which present up-to-date software applications, such as JMP®, SAS, and Design-Expert®, throughout An extensive references section to help readers stay up-to-date with leading research in the field of RSM An ideal textbook for upper-undergraduate and graduate-level courses in statistics, engineering, and chemical/physical sciences, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition is also a useful reference for applied statisticians and engineers in disciplines such as quality, process, and chemistry.

Empirical Model-Building and Response Surfaces
Empirical Model-Building and Response Surfaces

Author: George E. P. Box

Publisher: Wiley-Blackwell

Published: 1987-01-16

Total Pages: 696

ISBN-13:

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An innovative discussion of building empirical models and the fitting of surfaces to data. Introduces the general philosophy of response surface methodology, and details least squares for response surface work, factorial designs at two levels, fitting second-order models, adequacy of estimation and the use of transformation, occurrence and elucidation of ridge systems, and more. Some results are presented for the first time. Includes real-life exercises, nearly all with solutions.

The Construction of Optimal Stated Choice Experiments
The Construction of Optimal Stated Choice Experiments

Author: Deborah J. Street

Publisher: John Wiley & Sons

Published: 2007-07-20

Total Pages: 344

ISBN-13: 0470148551

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The most comprehensive and applied discussion of stated choice experiment constructions available The Construction of Optimal Stated Choice Experiments provides an accessible introduction to the construction methods needed to create the best possible designs for use in modeling decision-making. Many aspects of the design of a generic stated choice experiment are independent of its area of application, and until now there has been no single book describing these constructions. This book begins with a brief description of the various areas where stated choice experiments are applicable, including marketing and health economics, transportation, environmental resource economics, and public welfare analysis. The authors focus on recent research results on the construction of optimal and near-optimal choice experiments and conclude with guidelines and insight on how to properly implement these results. Features of the book include: Construction of generic stated choice experiments for the estimation of main effects only, as well as experiments for the estimation of main effects plus two-factor interactions Constructions for choice sets of any size and for attributes with any number of levels A discussion of designs that contain a none option or a common base option Practical techniques for the implementation of the constructions Class-tested material that presents theoretical discussion of optimal design Complete and extensive references to the mathematical and statistical literature for the constructions Exercise sets in most chapters, which reinforce the understanding of the presented material The Construction of Optimal Stated Choice Experiments serves as an invaluable reference guide for applied statisticians and practitioners in the areas of marketing, health economics, transport, and environmental evaluation. It is also ideal as a supplemental text for courses in the design of experiments, decision support systems, and choice models. A companion web site is available for readers to access web-based software that can be used to implement the constructions described in the book.

Robust Response Surfaces, Regression, and Positive Data Analyses
Robust Response Surfaces, Regression, and Positive Data Analyses

Author: Rabindra Nath Das

Publisher: CRC Press

Published: 2014-05-21

Total Pages: 333

ISBN-13: 1466506806

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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

Experiments with Mixtures
Experiments with Mixtures

Author: John A. Cornell

Publisher: John Wiley & Sons

Published: 2011-09-20

Total Pages: 682

ISBN-13: 111815049X

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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 StatisticalInstitute) "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

Response Surface Methodology
Response Surface Methodology

Author: Raymond H. Myers

Publisher: John Wiley & Sons

Published: 2016-01-04

Total Pages: 855

ISBN-13: 1118916026

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Praise for the Third Edition: “This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern applications of RSM.” - Zentralblatt Math Featuring a substantial revision, the Fourth Edition of Response Surface Methodology: Process and Product Optimization Using Designed Experiments presents updated coverage on the underlying theory and applications of response surface methodology (RSM). Providing the assumptions and conditions necessary to successfully apply RSM in modern applications, the new edition covers classical and modern response surface designs in order to present a clear connection between the designs and analyses in RSM. With multiple revised sections with new topics and expanded coverage, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition includes: Many updates on topics such as optimal designs, optimization techniques, robust parameter design, methods for design evaluation, computer-generated designs, multiple response optimization, and non-normal responses Additional coverage on topics such as experiments with computer models, definitive screening designs, and data measured with error Expanded integration of examples and experiments, which present up-to-date software applications, such as JMP®, SAS, and Design-Expert®, throughout An extensive references section to help readers stay up-to-date with leading research in the field of RSM An ideal textbook for upper-undergraduate and graduate-level courses in statistics, engineering, and chemical/physical sciences, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition is also a useful reference for applied statisticians and engineers in disciplines such as quality, process, and chemistry.

Response Surface Methodology and Related Topics
Response Surface Methodology and Related Topics

Author: Andr‚ I. Khuri

Publisher: World Scientific

Published: 2006

Total Pages: 474

ISBN-13: 9812774734

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This is the first edited volume on response surface methodology (RSM). It contains 17 chapters written by leading experts in the field and covers a wide variety of topics ranging from areas in classical RSM to more recent modeling approaches within the framework of RSM, including the use of generalized linear models. Topics covering particular aspects of robust parameter design, response surface optimization, mixture experiments, and a variety of new graphical approaches in RSM are also included. The main purpose of this volume is to provide an overview of the key ideas that have shaped RSM, and to bring attention to recent research directions and developments in RSM, which can have many useful applications in a variety of fields. The volume will be very helpful to researchers as well as practitioners interested in RSM''s theory and potential applications. It will be particularly useful to individuals who have used RSM methods in the past, but have not kept up with its recent developments, both in theory and applications. Sample Chapter(s). Chapter 1: Two-Level Factorial and Fractional Factorial Designs in Blocks of Size Two. Part 2 (560 KB). Contents: Two-Level Factorial and Fractional Factorial Designs in Blocks of Size Two. Part 2 (Y J Yang & N R Draper); Response Surface Experiments on Processes with High Variation (S G Gilmour & L A Trinca); Random Run Order, Randomization and Inadvertent Split-Plots in Response Surface Experiments (J Ganju & J M Lucas); Statistical Inference for Response Surface Optima (D K J Lin & J J Peterson); A Search Method for the Exploration of New Regions in Robust Parameter Design (G Mer-Quesada & E del Castillo); Response Surface Approaches to Robust Parameter Design (T J Robinson & S S Wulff); Response Surface Methods and Their Application in the Treatment of Cancer with Drug Combinations: Some Reflections (K S Dawson et al.); Generalized Linear Models and Response Transformation (A C Atkinson); GLM Designs: The Dependence on Unknown Parameters Dilemma (A I Khuri & S Mukhopadhyay); Design for a Trinomial Response to Dose (S K Fan & K Chaloner); Evaluating the Performance of Non-Standard Designs: The San Cristobal Design (L M Haines); 50 Years of Mixture Experiment Research: 1955OCo2004 (G F Piepel); Graphical Methods for Comparing Response Surface Designs for Experiments with Mixture Components (H B Goldfarb & D C Montgomery); Graphical Methods for Assessing the Prediction Capability of Response Surface Designs (J J Borkowski); Using Fraction of Design Space Plots for Informative Comparisons between Designs (C M Anderson-Cook & A Ozol-Godfrey); Concepts of Slope-Rotatability for Second Order Response Surface Designs (S H Park); Design of Experiments for Estimating Differences between Responses and Slopes of the Response (S Huda). Readership: Researchers in academia and industry interested in response surface methodology and its applications; engineers interested in improving quality and productivity in industry."

Handbook of Design and Analysis of Experiments
Handbook of Design and Analysis of Experiments

Author: Angela Dean

Publisher: CRC Press

Published: 2015-06-26

Total Pages: 946

ISBN-13: 146650434X

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This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.