19086
Lecture
SoSe 14: Optimal experimental designs
Guillaume Sagnol
Information for students
Nähere Informationen finden Sie auf der Homepage der Vorlesung.
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Content
Optimal design of experiments is a domain at the interface between mathematical optimization and statistics. It studies how to optimally select experiments, when the goal is to obtain the most accurate estimation of some unkwnown parameter.
The field of optimal experimental designs is interdisciplinary in nature, and involes a unique mixture of linear algebra, geometry, mathematical programming, statistics, and graph theory.
In this course, we will review classical results from the litterature on optimal experimental designs, with an important focus on the underlying geometry of the problem. Covered topics will include
- Introduction to linear models and applications
- Linear Algebra and Geometry of confidence ellipsoids
- Standard Optimality Criterions
- General Equivalence theorem
- Optimal Design for Polynomial Regression
- Algorithms for the construction of optimal designs
- Introduction to Semidefinite Programming (SDP)
- Combinatorics of block designs, relation with graph theory
- Optimal design for nonlinear experiments (Bayesian and minimax designs)
- Optimal design for model discrimination
14 Class schedule
Regular appointments
Wed, 2014-04-16 10:00 - 12:00
Wed, 2014-04-23 10:00 - 12:00
Wed, 2014-04-30 10:00 - 12:00
Wed, 2014-05-07 10:00 - 12:00
Wed, 2014-05-14 10:00 - 12:00
Wed, 2014-05-21 10:00 - 12:00
Wed, 2014-05-28 10:00 - 12:00
Wed, 2014-06-04 10:00 - 12:00
Wed, 2014-06-11 10:00 - 12:00
Wed, 2014-06-18 10:00 - 12:00
Wed, 2014-06-25 10:00 - 12:00
Wed, 2014-07-02 10:00 - 12:00
Wed, 2014-07-09 10:00 - 12:00
Wed, 2014-07-16 10:00 - 12:00
Content
Optimal design of experiments is a domain at the interface between mathematical optimization and statistics. It studies how to optimally select experiments, when the goal is to ... read more