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Verfasst von:Messer, Michael [VerfasserIn]   i
 Kirchner, Marietta [VerfasserIn]   i
Titel:A multiple filter test for the detection of rate changes in renewal processes with varying variance
Verf.angabe:Michael Messer, Marietta Kirchner, Julia Schiemann, Jochen Roeper, Ralph Neininger and Gaby Schneider
E-Jahr:2014
Jahr:19 December 2014
Umfang:41 S.
Fussnoten:Gesehen am 28.10.2020
Titel Quelle:Enthalten in: The annals of applied statistics
Ort Quelle:Beachwood, Ohio : Inst. of Mathematical Statistics (IMS), 2007
Jahr Quelle:2014
Band/Heft Quelle:8(2014), 4, Seite 2027-2067
ISSN Quelle:1941-7330
Abstract:Nonstationarity of the event rate is a persistent problem in modeling time series of events, such as neuronal spike trains. Motivated by a variety of patterns in neurophysiological spike train recordings, we define a general class of renewal processes. This class is used to test the null hypothesis of stationary rate versus a wide alternative of renewal processes with finitely many rate changes (change points). Our test extends ideas from the filtered derivative approach by using multiple moving windows simultaneously. To adjust the rejection threshold of the test, we use a Gaussian process, which emerges as the limit of the filtered derivative process. We also develop a multiple filter algorithm, which can be used when the null hypothesis is rejected in order to estimate the number and location of change points. We analyze the benefits of multiple filtering and its increased detection probability as compared to a single window approach. Application to spike trains recorded from dopamine midbrain neurons in anesthetized mice illustrates the relevance of the proposed techniques as preprocessing steps for methods that assume rate stationarity. In over 70% of all analyzed spike trains classified as rate nonstationary, different change points were detected by different window sizes.
DOI:doi:10.1214/14-AOAS782
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1214/14-AOAS782
 Volltext: https://projecteuclid.org/euclid.aoas/1419001734
 DOI: https://doi.org/10.1214/14-AOAS782
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:change point detection
 multiple filters
 multiple time scales
 nonstationary rate
 renewal processes
 Stochastic processes
K10plus-PPN:1736873539
Verknüpfungen:→ Zeitschrift

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