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Modeling and Inverse Problems in the Presence of Uncertainty
book

Modeling and Inverse Problems in the Presence of Uncertainty

by H. T. Banks, Shuhua Hu, W. Clayton Thompson
April 2014
Intermediate to advanced content levelIntermediate to advanced
405 pages
13h
English
Chapman and Hall/CRC
Content preview from Modeling and Inverse Problems in the Presence of Uncertainty
334 Modeling and Inverse Problems in the Presence of Uncertainty
Remark 8.4.1 Using the resulting deterministic model (8.36) the authors in
[43] discussed how to select a parameter subset combination that can be es-
timated using an ordinary least squares or generalized least squares method
with given VRE surveillance data from an oncology unit. Note that model
parameters in the stochastic VRE model are ex actly the same as those in the
deterministic one. Hence, this leads to rather obvious parameter estimation
techniques for CTMC models, that is, a method for estimating parameters in
CTMC models based on Kurtz’s limit theorem coupled with the inverse ...
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Publisher Resources

ISBN: 9781482206432