Comparing probabilistic methods for outlier detection

Irwin Guttman
Authors registered in the RePEc Author Service: Daniel Peña

UC3M Working papers. Economics from Universidad Carlos III de Madrid. Departamento de Economía

Abstract: This paper compares the use of two posterior probability methods to deal with outliers in linear models. We show that putting together diagnostics that come from the mean-shift and variance-shift models yields a procedure that seems to be more effective than the use of probabilities computed from the posterior distributions of actual realized residuals. The relation of the suggested procedure to the use of a certain predictive distribution for diagnostics is derived.

Keywords: Diagnostic; Posterior; and; Predictive; distributions; Leverage; Linear; models (search for similar items in EconPapers)
Date: 1992-07
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Persistent link: https://EconPapers.repec.org/RePEc:cte:werepe:2841

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