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On the number of outliers in data from a linear model

  • Sensitivity to Models
  • Invited Papers
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Trabajos de Estadistica Y de Investigacion Operativa

Summary

This paper reviews models for the occurrence of outliers in data from the linear model. The Bayesian analyses are all closely similar in form, but differ in the way they treat suspected outliers. The models are compared on Darwin’s data and one of them is used on data from a 25 factorial experiment.

The question of how many outliers are present involves comparison of models with different numbers of parameters. A solution using proper priors on all parameters is given. On two trial datasets it is found to be insensitive to choice of priors on all except the parameters representing the amount of contamination in the outliers. Here, choice of even a slightly “wrong” prior can be very misleading. Moreover, it is difficult to choose an appropriate prior when contaminations can be both positive or negative.

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Authors and Affiliations

  1. University of Leicester, Leicester, UK

    P. R. Freeman

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  1. P. R. Freeman
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Freeman, P.R. On the number of outliers in data from a linear model. Trabajos de Estadistica Y de Investigacion Operativa 31, 349–365 (1980). https://doi.org/10.1007/BF02888359

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  • DOI: https://doi.org/10.1007/BF02888359

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