A multiple filter test for the detection of rate changes in renewal processes with varying variance

The thesis provides novel procedures in the statistical field of change point detection in time series.
Motivated by a variety of neuronal spike train patterns, a broad stochastic point process model is introduced. This
The thesis provides novel procedures in the statistical field of change point detection in time series.
Motivated by a variety of neuronal spike train patterns, a broad stochastic point process model is introduced. This model features points in time (change points), where the associated event rate changes. For purposes of change point detection, filtered derivative processes (MOSUM) are studied. Functional limit theorems for the filtered derivative processes are derived. These results are used to support novel procedures for change point detection; in particular, multiple filters (bandwidths) are applied simultaneously in oder to detect change points in different time scales. 
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Metadaten
Author:Michael Messer
URN:urn:nbn:de:hebis:30:3-343947
Publisher:Univ.-Bibliothek
Place of publication:Frankfurt am Main
Referee:Gaby Schneider, Anton Wakolbinger, Roland Fried
Document Type:Doctoral Thesis
Language:English
Date of Publication (online):2014/06/30
Year of first Publication:2014
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Granting Institution:Johann Wolfgang Goethe-Universität
Date of final exam:2014/06/25
Release Date:2014/07/02
Pagenumber:150
HeBIS PPN:342617532
Institutes:Mathematik
Dewey Decimal Classification:570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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