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Factorial design plays a fundamental role in efficient and economic experimentation with multiple input variables and is extremely popular in various fields of application, including engineering, agriculture, medicine and life sciences. Factorial experiments are often used in case studies in quality management and Design for Six Sigma (DFSS). The last twenty years have witnessed a significant growth of interest in optimal factorial designs, under possible model uncertainty, via the minimum aberration and related criteria. The present book gives, for the first time in book form, a comprehensive and up-to-date account of this modern theory. Many major classes of designs are covered in the book. While maintaining a high level of mathematical rigor, it also provides extensive design tables for research and practical purposes. In order to equip the readers with the necessary background, some foundational concepts and results are developed in Chapter 2. Apart from being useful to researchers and practitioners, the book can form the core of a graduate level course in experimental design. It can also be used for courses in combinatorial designs or combinatorial mathematics.
| Autorius: | C. F. J. Wu, Rahul Mukerjee, |
| Serija: | Springer Series in Statistics |
| Leidėjas: | Springer US |
| Išleidimo metai: | 2010 |
| Knygos puslapių skaičius: | 236 |
| ISBN-10: | 144192180X |
| ISBN-13: | 9781441921802 |
| Formatas: | 235 x 155 x 13 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „A Modern Theory of Factorial Design“
