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Experimental design is an important branch of statistics with a long history, and is extremely useful in multi-factor experiments. Involving rich methodologies and various designs, it has played a key role in industry, technology, sciences and various other fields. A design that chooses experimental points uniformly scattered on the domain is known as uniform experimental design, and uniform experimental design can be regarded as a fractional factorial design with model uncertainty, a space-filling design for computer experiments, a robust design against the model specification, and a supersaturated design and can be applied to experiments with mixtures.
Experimental design is an important branch of statistics with a long history, and is extremely useful in multi-factor experiments. Involving rich methodologies and various designs, it has played a key role in industry, technology, sciences and various other fields. A design that chooses experimental points uniformly scattered on the domain is known as uniform experimental design, and uniform experimental design can be regarded as a fractional factorial design with model uncertainty, a space-filling design for computer experiments, a robust design against the model specification, and a supersaturated design and can be applied to experiments with mixtures.
Min-Qian Liu is a professor at the Institute of Statistics, Nankai University, Tianjin, China
Hong Qin is a professor at the Faculty of Mathematics and Statistics, Central China Normal
University, Wuhan, China
Yong-Dao Zhou is a professor at the Institute of Statistics, Nankai University, Tianjin, China
Equips readers with key idea and method of the uniform experimental design
Reviews the subject in both theoretical and applied aspects
Discusses measures of uniformity, various construction methods of uniform designs, modeling Techniques, design and modeling for experiments with mixtures, and the usefulness of the Uniformity in block, factorial and supersaturated designs
| Erscheinungsjahr: | 2018 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Importe, Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Reihe: | Lecture Notes in Statistics |
| Inhalt: |
xvi
300 S. 16 s/w Illustr. 30 farbige Illustr. 300 p. 46 illus. 30 illus. in color. |
| ISBN-13: | 9789811320408 |
| ISBN-10: | 9811320403 |
| Sprache: | Englisch |
| Herstellernummer: | 978-981-13-2040-8 |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Fang, Kai-Tai
Liu, Min-Qian Qin, Hong Zhou, Yong-Dao |
| Hersteller: |
Springer
Lecture Notes in Statistics |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 18 mm |
| Von/Mit: | Kai-Tai Fang (u. a.) |
| Erscheinungsdatum: | 02.10.2018 |
| Gewicht: | 0,482 kg |
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