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On Changepoint Detection in a Series of Stimulus-Response Data

  • In this paper, we demonstrate the power of functional data models for a statistical analysis of stimulus-response experiments which is a quite natural way to look at this kind of data and which makes use of the full information available. In particular, we focus on the detection of a change in the mean of the response in a series of stimulus-response curves where we also take into account dependence in time.

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Metadaten
Author:Euna Gesare Nyarige, Jürgen Franke, Alexander Fischer
URN (permanent link):urn:nbn:de:hbz:386-kluedo-51399
Serie (Series number):Report in Wirtschaftsmathematik (WIMA Report) (165)
Document Type:Article
Language of publication:English
Publication Date:2018/01/30
Year of Publication:2018
Publishing Institute:Technische Universität Kaiserslautern
Date of the Publication (Server):2018/01/31
Tag:changepoint test; functional data; functional time series; inhibitory synaptic transmission; stimulus response data
Number of page:19
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:5 Naturwissenschaften und Mathematik / 510 Mathematik
MSC-Classification (mathematics):62-XX STATISTICS
Licence (German):Creative Commons 4.0 - Namensnennung, nicht kommerziell, keine Bearbeitung (CC BY-NC-ND 4.0)