Nonparametric inference for continuous-time event counting and link-based dynamic network models
A flexible approach for modeling both dynamic event counting and dynamic link-based networks based on counting processes is proposed, and estimation in these models is studied. We consider nonparametric likelihood based estimation of parameter functions via kernel smoothing. The asymptotic behavior...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Dokumenttyp: | Article (Journal) Chapter/Article |
| Sprache: | Englisch |
| Veröffentlicht: |
4 Jul 2017
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| In: |
Arxiv
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| Online-Zugang: | kostenfrei
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| Verfasserangaben: | Alexander Kreiß, Enno Mammen, Wolfgang Polonik |
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