Calibration and Prediction

  • Sylvie Huet
  • Annie Bouvier
  • Marie-Anne Gruet
  • Emmanuel Jolivet
Part of the Springer Series in Statistics book series (SSS)

Abstract

In this chapter, we describe how to calculate prediction and calibration confidence intervals. These intervals account for the double source of variability that exists in this type of experiment: the variability of the response about its mean, and the uncertainty about the regression parameters.

Keywords

Maximum Likelihood Estimator Bootstrap Sample Prediction Interval Asymptotic Level Bootstrap Simulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [GHJ93]
    M.A. Gruet, S. Huet, and E. Jolivet. Practical use of bootstrap in regression. In W. Härdle and L. Simar, editors, Computer Intensive Methods in Statistics, pages 150–166. Physica-Verlag, Heidelberg, 1993.Google Scholar
  2. [GJ94]
    M.A. Gruet and E. Jolivet. Calibration with a nonlinear standard curve: how to do it? Computational Statistics, 9: 249–276, 1994.MathSciNetMATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Sylvie Huet
    • 1
  • Annie Bouvier
    • 1
  • Marie-Anne Gruet
    • 1
  • Emmanuel Jolivet
    • 2
  1. 1.INRA Laboratoire de BiométrieJouy-en-Josas CedexFrance
  2. 2.INRA SESAMESParis Cedex 07France

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