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SUMMARY:Exploring ODE model uncertainty via diffusions\, with application 
 to physiological processes - Dr Kostas Kalogeropoulos\, London School of E
 conomics
DTSTART:20100519T090000Z
DTEND:20100519T100000Z
UID:TALK23715@talks.cam.ac.uk
CONTACT:Rachel Fogg
DESCRIPTION:Ordinary differential equations models are extensively used to
  describe various continuous time phenomena. Although successful in captur
 ing certain aspects of the underlying mechanism\, the need for further ref
 inement is becoming increasing apparent. In many applications\, including 
 our motivating example from physiological processes\, this may be attribut
 ed to the inherent system noise. In our approach the system noise is expli
 citly modelled and disentangled from other sources of error. This is achie
 ved by incorporating a diffusive component while retaining the mean infini
 tesimal behavior of the system. In PK/PD applications\, the problem of inf
 erence on the non linear diffusion parameters is further complicated by th
 e presence of measurement error\, individual variability\, imbalanced desi
 gns and so forth. We present a general inference framework through data au
 gmentation which we illustrate through simulated and real PK/PD data.
LOCATION:LR12\, Engineering\, Department of
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