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Diskrimination und Klassifikation von Verlaufskurven

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Neuere Verfahren der nichtparametrischen Statistik

Part of the book series: Medizinische Informatik und Statistik ((MEDINFO,volume 60))

Zusammenfassung

Für viele Fragestellungen der statistischen Praxis sind Verlaufskurven das einfachste Objekt der Beobachtung. Wir verstehen darunter das folgende Modell

$$ {\text{Y(t) = f(t) + Z(t) a}} \leqslant {\text{t}} \leqslant {\text{b}} $$
(1.1)

Dabei ist Y(t) der Prozeß, der zu bestimmten Zeitpunkten t1…,tn beobachtet wird, f(t) ist eine unbekannte Regressionsfunktion, die den Verlauf des interessierenden Phänomens beschreibt und Z(t) ist ein stochastischer Störprozeß, dessen Mittelwertsfunktion E(Z(t)) konstant O ist.

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Authors
  1. W. Grossmann
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Editors and Affiliations

  1. Mathematisches Institut, Justus-Liebig-Universität, Arndtstraße 2, 6300, Gießen, Deutschland

    Georg Ch. Pflug

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© 1985 Springer-Verlag Berlin Heidelberg

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Grossmann, W. (1985). Diskrimination und Klassifikation von Verlaufskurven. In: Pflug, G.C. (eds) Neuere Verfahren der nichtparametrischen Statistik. Medizinische Informatik und Statistik, vol 60. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-70641-7_7

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  • DOI: https://doi.org/10.1007/978-3-642-70641-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-15702-1

  • Online ISBN: 978-3-642-70641-7

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