Neural Network Based Lag Selection, for Multivariate Time Series

  • In this work we present and estimate an explanatory model with a predefined system of explanatory equations, a so called lag dependent model. We present a locally optimal, on blocked neural network based lag estimator and theorems about consistensy. We define the change points in context of lag dependent model, and present a powerfull algorithm for change point detection in high dimensional high dynamical systems. We present a special kind of bootstrap for approximating the distribution of statistics of interest in dependent processes.
  • Auf neuronalen Netzen basierte Suche nach Totzeiten in multivarianten Zeitreihen

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Metadaten
Author:Alex Sarishvili
URN (permanent link):urn:nbn:de:bsz:386-kluedo-15096
Advisor:Jürgen Franke
Document Type:Doctoral Thesis
Language of publication:English
Year of Completion:2002
Year of Publication:2002
Publishing Institute:Technische Universität Kaiserslautern
Granting Institute:Technische Universität Kaiserslautern
Acceptance Date of the Thesis:2002/02/26
Tag:Neural Networks ; Nonlinear time series analysis ; time delays
GND-Keyword:ITSM; Neuronales Netz ; Time-delay-Netz
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:510 Mathematik

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