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A Quasi Bayesian Approach to Outlier Detection

  • Genshiro Kitagawa
  • Hirotugu Akaike
Part of the Springer Series in Statistics book series (SSS)

Summary

A quasi Bayesian procedure is developed for the detection of outliers. A particular Gaussian distribution with ordered means is assumed as the basic model of the data distribution. By introducing a definition of the likelihood of a model whose parameters are determined by the method of maximum likelihood, the posterior probability of the model is obtained for a particular choice of the prior probability distribution. Numerical examples are given to illustrate the practical utility of the procedure.

Keywords

Posterior Probability Prior Probability Outlier Detection Order Restriction Prior Probability Distribution 
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 Science+Business Media New York 1998

Authors and Affiliations

  • Genshiro Kitagawa
  • Hirotugu Akaike

There are no affiliations available

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