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

Date: 12:30 06 March 2018 - 13:30 06 March 2018
Type: Seminar
Speaker: Enno Mammen University of Mannheim
Venue: Institute for Fiscal Studies
Prices: Free


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.

Paper: https://arxiv.org/pdf/1705.03830.pdf

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