Seminar: Wasiur KhudaBukhsh - Further progress on survival dynamical systems

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March 31, 2020
10:20AM - 11:15AM
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Add to Calendar 2020-03-31 10:20:00 2020-03-31 11:15:00 Seminar: Wasiur KhudaBukhsh - Further progress on survival dynamical systems Wasiur KhudaBukhsh Postdoctoral Fellow, MBI Solutions to ordinary differential equations (ODEs) describing the large-population limits of Markovian stochastic epidemic models can be interpreted as survival or cumulative hazard functions when analysing data on individuals sampled from the population. We refer to the individual-level survival and hazard functions derived from population-level equations as a Survival Dynamical System (SDS). I will report some progress on developing an SDS methodology for non-Markovian dynamics. Measure-valued processes play a key role in this endeavour. For the non-Markovian set-up, the SDS-likelihood is shown to depend on solutions to partial differential equations instead of ODEs as before. Preliminary numerical results for SDS likelihood-based parameter inference will be shown. Finally, I will discuss an extension to non-Markovian epidemics on configuration model random graphs. This event has been postponed. THIS EVENT HAS BEEN POSTPONED Mathematical Biosciences Institute mbi-webmaster@osu.edu America/New_York public
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Wasiur KhudaBukhsh

Postdoctoral Fellow, MBI


Solutions to ordinary differential equations (ODEs) describing the large-population limits of Markovian stochastic epidemic models can be interpreted as survival or cumulative hazard functions when analysing data on individuals sampled from the population. We refer to the individual-level survival and hazard functions derived from population-level equations as a Survival Dynamical System (SDS).

I will report some progress on developing an SDS methodology for non-Markovian dynamics. Measure-valued processes play a key role in this endeavour. For the non-Markovian set-up, the SDS-likelihood is shown to depend on solutions to partial differential equations instead of ODEs as before. Preliminary numerical results for SDS likelihood-based parameter inference will be shown. Finally, I will discuss an extension to non-Markovian epidemics on configuration model random graphs.

This event has been postponed.

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