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Comparison with Extremely Informative Experiments

  • H. Heyer
Part of the Springer Series in Statistics book series (SSS)

Abstract

The topic of this section refers to the comparison of experiments with respect to apriori measures which have been introduced in Section 3. There we formulated the Bayesian principle as one of the basic ideas of modern statistics. Although we did not put much emphasis on the Bayesian approach throughout the exposition we intend at least to touch upon the general scope in handling a few interesting types of examples: We shall study deviations from total information and from total ignorance as measures of information. In other words we shall compute the deficiencies of experiments relative to totally informative and totally uninformative ones respectively. For the corresponding computations apriori distributions are of great value.

Keywords

Stochastic Matrix Stochastic Matrice Stochastic Kernel Informative Experiment Tolerance Function 
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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Copyright information

© Springer-Verlag New York Inc. 1982

Authors and Affiliations

  • H. Heyer
    • 1
  1. 1.Mathematisches InstitutUniversität TübingenTübingen 1West Germany

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