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Multivariate Regression and ANOVA Models with Outliers: A Comparative Approach

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  • Polasek, Wolfgang

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna)

Abstract

Assuming a normal-Wishart modelling framework we compare two methods for finding outliers in a multivariate regression (MR) system. One method is the add-1-dummy approach which needs fewer parameters and a model choice criterion while the other method estimates the outlier probability for each observation by a Bernoulli mixing outlier location shift model. For the simple add-1-dummy model the Bayes factors and the posterior probabilities can be calculated explicitly. In the probabilistic mixing model we show how the posterior distribution can be obtained by a Gibbs sampling algorithm. The number of outliers is determined using the marginal likelihood criterion. The methods are compared for test scores of language examination data of Fuller (1987): The results are similar but differ in their strength of their empirical evidence.

Suggested Citation

  • Polasek, Wolfgang, 2003. "Multivariate Regression and ANOVA Models with Outliers: A Comparative Approach," Economics Series 136, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihsesp:136
    as

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    File URL: https://irihs.ihs.ac.at/id/eprint/1510
    File Function: First version, 2003
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    References listed on IDEAS

    as
    1. Wolfgang Polasek, "undated". "Structural Breaks and VAR Modeling with Marginal Likelihoods," Computing in Economics and Finance 1997 50, Society for Computational Economics.
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    More about this item

    Keywords

    Multivariate regression; Multivariate one-way ANOVA; Outliers; Gibbs sampling; Marginal likelihoods; Sensitivity analysis;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other

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