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Optimal Experimental Design for Non-Linear Models [electronic resource] : Theory and Applications / by Christos P. Kitsos.

By: Kitsos, Christos P [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Statistics: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: IX, 102 p. 8 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642452871.Subject(s): Statistics | Statistics | Statistics, generalDDC classification: 519.5 Online resources: Click here to access online
Contents:
1.Introduction -- 2. Motivation -- 3.Locally Optimal Designs -- 4.Static Design -- 5.Sequential Designs -- 6.Approximate Confidence Regions -- 7.Working with Data: Simulation Studies -- 8.A Case Study: Optimal Designs in Rythmometry -- 9.Discussion -- References -- A1.Caratheodory’s Theorem -- A2.Silvapulle's Theorem -- A3.Conditional Inverse -- A4.Simulation I Results, Tables 7.1 – 7.5 -- A5.Simulation II Results, Tables 7.7 – 7.14.
In: Springer eBooksSummary: This book tackles the Optimal Non-Linear Experimental Design problem from an applications perspective. At the same time it offers extensive mathematical background material that avoids technicalities, making it accessible to non-mathematicians: Biologists, Medical Statisticians, Sociologists, Engineers, Chemists and Physicists will find new approaches to conducting their experiments. The book is recommended for Graduate Students and Researchers.
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1.Introduction -- 2. Motivation -- 3.Locally Optimal Designs -- 4.Static Design -- 5.Sequential Designs -- 6.Approximate Confidence Regions -- 7.Working with Data: Simulation Studies -- 8.A Case Study: Optimal Designs in Rythmometry -- 9.Discussion -- References -- A1.Caratheodory’s Theorem -- A2.Silvapulle's Theorem -- A3.Conditional Inverse -- A4.Simulation I Results, Tables 7.1 – 7.5 -- A5.Simulation II Results, Tables 7.7 – 7.14.

This book tackles the Optimal Non-Linear Experimental Design problem from an applications perspective. At the same time it offers extensive mathematical background material that avoids technicalities, making it accessible to non-mathematicians: Biologists, Medical Statisticians, Sociologists, Engineers, Chemists and Physicists will find new approaches to conducting their experiments. The book is recommended for Graduate Students and Researchers.

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