Dean / Morris / Stufken Handbook of Design and Analysis of Experiments

Erscheinungsjahr 2015
ISBN: 978-1-4665-0434-9
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 960 Seiten

Reihe: Chapman & Hall/CRC Handbooks of Modern Statistical Methods

Handbook of Design and Analysis of Experiments provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook gives a unified treatment of a wide range of topics, covering the latest developments.

This carefully edited collection of 25 chapters in seven sections synthesizes the state of the art in the theory and applications of designed experiments and their analyses. Written by leading researchers in the field, the chapters offer a balanced blend of methodology and applications.

The first section presents a historical look at experimental design and the fundamental theory of parameter estimation in linear models. The second section deals with settings such as response surfaces and block designs in which the response is modeled by a linear model, the third section covers designs with multiple factors (both treatment and blocking factors), and the fourth section presents optimal designs for generalized linear models, other nonlinear models, and spatial models. The fifth section addresses issues involved in designing various computer experiments. The sixth section explores "cross-cutting" issues relevant to all experimental designs, including robustness and algorithms. The final section illustrates the application of experimental design in recently developed areas.

This comprehensive handbook equips new researchers with a broad understanding of the field’s numerous techniques and applications. The book is also a valuable reference for more experienced research statisticians working in engineering and manufacturing, the basic sciences, and any discipline that depends on controlled experimental investigation.

Zielgruppe

Graduate students and researchers in statistics, industrial engineering, manufacturing, pharmaceutical industry, and life sciences.

Autoren/Hrsg.

Dean, Angela

Morris, Max

Stufken, John

Bingham, Derek

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik

Inhaltsverzeichnis

General Principles
History and Overview of Design and Analysis of Experiments Klaus Hinkelmann
Introduction to Linear Models Linda M. Haines

Designs for Linear Models
Blocking with Independent Responses John P. Morgan
Crossover Designs Mausumi Bose and Aloke Dey
Response Surface Experiments and Designs André I. Khuri and Siuli Mukhopadhyay
Design for Linear Regression Models with Correlated Errors Holger Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky

Designs Accommodating Multiple Factor
Regular Fractional Factorial Designs Robert Mee and Angela Dean
Multistratum Fractional Factorial Designs Derek Bingham
Nonregular Factorial and Supersaturated Designs Hongquan Xu
Structures Defined by Factors R.A. Bailey
Algebraic Method in Experimental Design Hugo Maruri-Aguilar and Henry P. Wynn

Optimal Design for Nonlinear and Spatial Models
Optimal Design for Nonlinear and Spatial Models: Introduction and Historical Overview Douglas P. Wiens
Designs for Generalized Linear Models Anthony C. Atkinson and David C. Woods
Designs for Selected Nonlinear Models Stefanie Biedermann and Min Yang
Optimal Design for Spatial Models Zhengyuan Zhu and Evangelos Evangelou

Computer Experiments
Design of Computer Experiments: Introduction and Background Max Morris and Leslie Moore
Latin Hypercubes and Space-Filling Designs C. Devon Lin and Boxin Tang
Design for Sensitivity Analysis William Becker and Andrea Saltelli
Expected Improvement Designs William I. Notz

Cross-Cutting Issues
Robustness of Design Douglas P. Wiens
Algorithmic Searches for Optimal Designs Abhyuday Mandal, Weng Kee Wong, and Yaming Yu

Design for Contemporary Applications
Design for Discrete Choice Experiments Heiko Grossmann and Rainer Schwabe
Plate Designs in High-Throughput Screening Experiments for Drug Discovery Xianggui Qu (Harvey) and Stanley Young
Up-and-Down Designs for Dose-Finding Nancy Flournoy and Assaf P. Oron
Optimal Design for Event-Related fMRI Studies Jason Ming-Hung Kao and John Stufken

Index

Über Autor(innen)

Angela Dean is professor emeritus in the Department of Statistics and a member of the Emeritus Academy at The Ohio State University. She is a fellow of the American Statistical Association and the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. Her primary research focuses on the design of screening experiments.

Max Morris is professor and chair of the Department of Statistics at Iowa State University, where he also holds a courtesy appointment in the Department of Industrial and Manufacturing Systems Engineering. He is a fellow of the American Statistical Association. His research program focuses on the design and analysis of experiments, with special emphasis on those that involve computer models.

John Stufken is the Charles Wexler Professor in Statistics in the School of Mathematical and Statistical Sciences at Arizona State University. He is a fellow of the American Statistical Association and the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. His primary area of research interest is the design and analysis of experiments.

Derek Bingham is professor in the Department of Statistics and Actuarial Science at Simon Fraser University, Burnaby. His primary research interests lie in the design and analysis of physical and computer experiments.