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12:30 - 13:30 6 March 2018

Nonparametric inference for event counting and link-based dynamic network models

Location

IFS Conference Room | 7 (link Map)
Ridgmount Street | London | London | WC1E 7AE | United Kingdom

Open to: Academic | Student
Admission: Free
Ticketing: Open

Speaker information

Enno Mammen, Heidelberg

A flexible class of time-varying link-based continuous-time random network models based on counting processes is considered, and a rigorous analysis of corresponding maximum likelihood estimators is presented. The model parameters are allowed to be functions of time. The presented asymptotic analysis assumes the time horizon tending to infinity. Our model allows for both Markovian and non-Markovian structures. We present results on asymptotic normality of corresponding local maximum likelihood estimators, and illustrate the finite sample performance of the estimation procedure through numerical studies. The talk reports on joint work with Alexander Kreiss, Heidelberg and Wolfgang Polonik, Davis.


Contact

IFS events
events@ifs.org.uk


Links

Seminar paper


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