Optimum designs for multi-factor models /
In real applications most experimental situations are influenced by a large number of different factors. In these settings the design of an experiment leads to challenging optimization problems, even if the underlying relationship can be described by a linear model. Based on recent research, this vo...
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| Format: | eBook |
| Language: | English |
| Published: |
New York :
Springer,
[1996]
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| Series: | Lecture notes in statistics (Springer-Verlag) ;
v. 113. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | In real applications most experimental situations are influenced by a large number of different factors. In these settings the design of an experiment leads to challenging optimization problems, even if the underlying relationship can be described by a linear model. Based on recent research, this volume introduces the theory of optimum designs for complex models. It also develops general methods of reduction of marginal problems for large classes of models with relevant interaction structures. Familiarity with the statistical theory of linear models is desirable, but not necessary. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (124 pages) |
| Format: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |
| Bibliography: | Includes bibliographical references (pages [113]-119) and index. |
| ISBN: | 9781461240389 (electronic bk.) 1461240387 (electronic bk.) |