Diagnostic measures for linear mixed measurement error models

• Autores: Karim Zare, Abdolrahman Rasekh
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 35, Nº. 2, 2011, págs. 125-144
• Idioma: inglés
• Enlaces
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• Resumen

  • In this paper, we present case deletion and mean shift outlier models for linear mixed measure- ment error models using the corrected likelihood of Nakamura (1990). We derive the corrected score test statistic for outliers detection based on mean shift outlier models. Furthermore, several case deletion diagnostics are constructed as a tool for influence diagnostics. It is found that they can be written in terms of studentized residuals of model, error contrast matrix and the inverse of the response variable covariance matrix. Our influence diagnostics are illustrated through a real data set.

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