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:urn:nbn:de:bsz:386-kluedo-15096
Advisor:Jürgen Franke
Document Type:Doctoral Thesis
Language of publication:English
Year of Completion:2002
Year of first Publication:2002
Publishing Institution:Technische Universität Kaiserslautern
Granting Institution:Technische Universität Kaiserslautern
Acceptance Date of the Thesis:2002/02/26
Date of the Publication (Server):2002/10/16
Tag:Neural Networks; Nonlinear time series analysis; time delays
GND Keyword:Neuronales Netz; Time-delay-Netz; ITSM
Faculties / Organisational entities:Kaiserslautern - Fachbereich Mathematik
DDC-Cassification:5 Naturwissenschaften und Mathematik / 510 Mathematik
Licence (German):Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011