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Handbook of design and analysis of experiments / [edited by] Angela Dean...[et al.]

Contributor(s): Material type: TextTextSeries: Chapman & Hall/CRC handbooks of modern statistical methodsPublication details: Boca Raton : CRC Press, ©2015.Description: xix, 940 p. : illustrations ; 26 cmISBN:
  • 9781466504332 (hbk.)
Subject(s): DDC classification:
  • 000SA.2 23 D281
Contents:
Section I General Prinicples -- 1. History and overview of design and analysis of experiments / Klaus Hinkelmann -- 2. Introduction to linear models / Linda M. Haines -- Section II Designs for Linear Models -- 3. Blocking with independent responses / John P. Morgan -- 4. Crossover designs / Mausumi Bose and Aloke Dey -- 5. Responses surface experiments and designs / Andre I. Khuri and Siuli Mukhopadhyay -- 6. Design for linear regression models with correlated errors / Hogler Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky -- Section III Designs Accommodating Multiple Factors -- 7. Regular fractional factorial designs / Robert Mee and Angela Dean -- 8. Multistratum fractional factorial designs / Derek Bingham -- 9. Nonregular factorial and supersaturated designs / Hongquam Xu -- 10. Structures defined by factors / R.A. Bailey -- 11. Algebraic method in experimental design / Hugo Maruri-Aguilar and Henry P. Wynn -- Section IV Optimal Design for Nonlinear and Spatial Models -- 12. Optimal design for nonlinear and spatial models: introduction and historical overview / Douglas P. Wiens -- 13. Designs for generalized linear models / Anthony C. Atkinson and David C. Woods -- 14. Designs for selected nonlinear models / Stefanie Bierdermann and Min Yang -- 15. Optimal design for spatial models / Zhengyuan Zhu and Evangelos Evangelou -- Section V Computer Experiments -- 16. Design of computer experiments: introduction and background / Max D. Morris and Leslie M. Moore -- 17. Latin hypercubes and space-filling designs / C. Devon Lin and Boxin Tang -- 18. Design for sensitivity analysis / William Becker and Andrea Saltelli -- 19. Expected improvement design / William I. Notz -- Section VI Cross-Cutting Issues -- 20. Robustness of design / Douglas P. Wiens -- 21. Algorithmic searches for optimal design / Abhyuday Mandal, Weng Kee Wong, and Yaming Yu -- Section VII Design for Contemporary Applications -- 22. Design for discrete choice experiments / Heiko Grossmann and Rainer Schwabe -- 23. Plate designs in high-throughput screening experiments for drug discovery / Xianggui Qu (Harvey) and Stanley Young -- 24. Up-and-down designs for dose-finding / Nancy Flournoy and Assaf P. Oron -- 25. Optimal design for event-related fMRI studies / Jason Ming-Hung Kao and John Stufken.
Summary: 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 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.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.2 D281 (Browse shelf(Opens below)) Available 137246
Total holds: 0

Includes bibliographical references and index.

Section I General Prinicples --
1. History and overview of design and analysis of experiments / Klaus Hinkelmann --
2. Introduction to linear models / Linda M. Haines --
Section II Designs for Linear Models --
3. Blocking with independent responses / John P. Morgan --
4. Crossover designs / Mausumi Bose and Aloke Dey --
5. Responses surface experiments and designs / Andre I. Khuri and Siuli Mukhopadhyay --
6. Design for linear regression models with correlated errors / Hogler Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky --
Section III Designs Accommodating Multiple Factors --
7. Regular fractional factorial designs / Robert Mee and Angela Dean --
8. Multistratum fractional factorial designs / Derek Bingham --
9. Nonregular factorial and supersaturated designs / Hongquam Xu --
10. Structures defined by factors / R.A. Bailey --
11. Algebraic method in experimental design / Hugo Maruri-Aguilar and Henry P. Wynn --
Section IV Optimal Design for Nonlinear and Spatial Models --
12. Optimal design for nonlinear and spatial models: introduction and historical overview / Douglas P. Wiens --
13. Designs for generalized linear models / Anthony C. Atkinson and David C. Woods --
14. Designs for selected nonlinear models / Stefanie Bierdermann and Min Yang --
15. Optimal design for spatial models / Zhengyuan Zhu and Evangelos Evangelou --
Section V Computer Experiments --
16. Design of computer experiments: introduction and background / Max D. Morris and Leslie M. Moore --
17. Latin hypercubes and space-filling designs / C. Devon Lin and Boxin Tang --
18. Design for sensitivity analysis / William Becker and Andrea Saltelli --
19. Expected improvement design / William I. Notz --
Section VI Cross-Cutting Issues --
20. Robustness of design / Douglas P. Wiens --
21. Algorithmic searches for optimal design / Abhyuday Mandal, Weng Kee Wong, and Yaming Yu --
Section VII Design for Contemporary Applications --
22. Design for discrete choice experiments / Heiko Grossmann and Rainer Schwabe --
23. Plate designs in high-throughput screening experiments for drug discovery / Xianggui Qu (Harvey) and Stanley Young --
24. Up-and-down designs for dose-finding / Nancy Flournoy and Assaf P. Oron --
25. Optimal design for event-related fMRI studies / Jason Ming-Hung Kao and John Stufken.

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 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.

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