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Some Criteria For Choosing a Procedure

  • Jack Carl Kiefer
Part of the Springer Texts in Statistics book series (STS)

Abstract

Having specified the statistics problem or model associated with an experiment with which we are concerned, we must select a single procedure t to be used with the data from that experiment. Since for most statistical problems there are no uniformly best procedures, some additional criterion (or criteria) is (are) necessary. The purpose of such a criterion is to specify uniquely a statistical procedure t which will be used. Some of the criteria which are often used to select a single procedure t to be used in a particular statistics problem are the following:
  1. 1.

    Bayes criterion

     
  2. 2.

    Minimax criterion

     
  3. 3.

    Invariance criterion

     
  4. 4.

    Unbiasedness criterion

     
  5. 5.

    Sufficiency criterion

     
  6. 6.

    Robustness criterion

     
  7. 7.

    Maximum likelihood and likelihood ratio methods

     
  8. 8.

    Method of moments

     
  9. 9.

    Criteria of asymptotic efficiency

     

Keywords

Risk Function Unbiased Estimator Prior Density Constant Risk Complete Class 
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. 1987

Authors and Affiliations

  • Jack Carl Kiefer

There are no affiliations available

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