Skip to main content
Springer Nature Link
Log in

Modellprüfung — Statistische Methoden

  • Conference paper
Simulationstechnik

Part of the book series: Informatik — Fachberichte ((INFORMATIK,volume 85))

  • 267 Accesses

Zusammenfassung

Das Studium von Prozessen in der realen Welt erfolgt anhand von Modellen, d. h. qualitativen oder quantitativen Repräsentationen des Prozesses, die die relevanten Einflußfaktoren erfassen sollen. Dabei werden die wesentlichen Eigenschaften des Prozesses und ihre Wechselwirkungen durch mathematische Symbole und Gesetze repräsentiert.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

Literatur

  • AKAIKE, H (1974). A new look at the Statistical model identification. I.E.E. E.Trans.Auto.Control AC-19, 716–723

    Article  MathSciNet  MATH  Google Scholar 

  • ATKINSON, AC, COX, DR (1974). Planning experiments for discriminating between models. J.R.Statist.Soc.B 36, 321–348.

    MathSciNet  MATH  Google Scholar 

  • ATKINSON, AC, FEDOROV, VV (1975a). The design of experiments for discriminating between two rival models. Biometrika 62, 57–70.

    Article  MathSciNet  MATH  Google Scholar 

  • ATKINSON, AC, FEDOROV, VV (1975b). Optimal design: Experiments for discriminating between several models. Biometrika 62, 289–303.

    MathSciNet  MATH  Google Scholar 

  • ANDERSON, TW (1971). The Statistical Analysis of Time Series. John Wiley & Sons, New York London Sidney Toronto.

    MATH  Google Scholar 

  • BAUER, P (1975). Zur Adäquatheitsprüfung von Modellen (II). Biom.Z.17, 345–362.

    Article  MATH  Google Scholar 

  • BAUER, P, HACKL, P (1978). The use of MOSUMs for quality control. Technometrics 20, 431–436.

    Article  MATH  Google Scholar 

  • BAUER, P, HACKL, P (1980). An extension of the MOSUM technique for quality control. Technometrics 22, 1–7.

    Article  MATH  Google Scholar 

  • BAUER, PS HACKL, P (1984). The application of HUNTER 1 s inequality in simultaneous testing. Biom.J. im Druck

    Google Scholar 

  • BAUER, P, HACKL, P(1984). A sequentially rejective test for the degree of a polynomial. Preprint University of Economics, Vienna.

    Google Scholar 

  • BOX, GEP, HILL, WJ (1976). Discriminating among mechanistic models. Technometrics 9, 57–71

    Article  MathSciNet  Google Scholar 

  • BROWN, RL, DURBIN, J, EVANS. JM (1975). Techniques for testing the constancy of regression relationships over time. J.Roy.Statist.Soc. B, 37, 194–192.

    MathSciNet  Google Scholar 

  • BUNKE, O, DROGE, B (1984). Estimators of the mean squared error of prediction in linear regression. Technometrics 26, 145–155.

    Article  MathSciNet  MATH  Google Scholar 

  • BUNKE, O, GRABOWSKY, B (1978). A procedure for model choice or variable selection with controlled model specification error. M.0.S.9, 483–497.

    Google Scholar 

  • CHERNOFF, H (1959). Sequential design of experiments. Ann.Math.Statist. 30, 755–770

    Article  MathSciNet  MATH  Google Scholar 

  • COX, DR (1962). Further results on tests of separate families of hypotheses. J.Roy.Statist.Soc.B 24, 406–424.

    MATH  Google Scholar 

  • FEDOROV, VV (1972). Theory of Optimal Experiments. Academic Press, New York and London

    Google Scholar 

  • FEDOROV, VV (1975). Optimal experimental design for discriminating two rival regression models. In: A Survey of Statistical Design and Linear Models. Ed. JN Srivastava, North-Holland Publishing Company.

    Google Scholar 

  • GROSSMANN, W (1982). Statistical estimation of nonlinear regression functions. Math.Operationsforsch.Statist.,Ser.Statistics 13, 455–471 .

    MathSciNet  MATH  Google Scholar 

  • HACKL, P (1980) Testing the Constancy of Regression Models over Time. Vandenhoeck & Ruprecht Göttingen.

    MATH  Google Scholar 

  • HOLM, S (1979) A simple sequentially rejective multiple test procedure. Scand.J.Statist.6, 65–70.

    MathSciNet  MATH  Google Scholar 

  • HUNTER, WG, REINER, AM (1965). Design for discriminating between two rival models. Technometrics 7, 307–323

    Article  MathSciNet  Google Scholar 

  • KRAAFT, O (1978). Lineare statistische Modelle und optimale Versuchspläne. Vandenhoeck & Ruprecht Göttingen und Zürich

    Google Scholar 

  • PLOBERGER, W (1984) Testing the constancy of parameters in linear models. Research Report 22, Department of Economics, TU Wien

    Google Scholar 

  • MALLOWS, CL (1973) Some comments on Cp. Technometrics 15, 661-675.

    Article  MATH  Google Scholar 

  • SEARLE, SR (1971). Linear models. John Wiley & Sons, New York London Sidney Toronto.

    MATH  Google Scholar 

  • WALD, A (1947) . Sequential analysis. John Wiley & Sons, Chapman & Hall, London

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institut für medizinische Statistik und Dokumentation, A-1090, Schwarzspanierstraße 17, Wien, Austria

    P. Bauer

Authors
  1. P. Bauer
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institut für Technische Mathematik, Technische Universität Wien, Wiedner Hauptstraße 8-10, A-1040, Wien, Austria

    Felix Breitenecker

  2. Hybriddrechenzentrum, Technische Universität Wien, Gußhausstraße 27-29, A-1040, Wien, Austria

    Wolfgang Kleinbert

Rights and permissions

Reprints and permissions

Copyright information

© 1984 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bauer, P. (1984). Modellprüfung — Statistische Methoden. In: Breitenecker, F., Kleinbert, W. (eds) Simulationstechnik. Informatik — Fachberichte, vol 85. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-69706-7_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-69706-7_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-13393-3

  • Online ISBN: 978-3-642-69706-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy