Friday, 10:30 - 10:55 h, Room: MA 376


Max Nattermann
A quadratic approximation of confidence regions

Coauthor: Ekaterina Kostina


Dealing with the task of identifying unknown quantities from a set of erroneous data, the performance of a sensitivity analysis is inevitable. Without the determination of the statistical accuracy, we are not able to make any quality statements about the estimate. Consequently the result is almost meaningless. Commonly one applies linearization techniques to determine the statistical accuracy of the solution. But particularly in highly nonlinear cases this may cause problems and linear confidence regions may not be adequate.
In this talk, we are going to present and analyze a confidence region based on a quadratic approximation. Furthermore, we demonstrate our results using applications from biology. Furthermore, we discuss the impact of the new results to optimum experimental design.


Talk 1 of the contributed session Fri.1.MA 376
"Model discrimination and experimental design" [...]
Cluster 12
"Life sciences & healthcare" [...]


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