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Giummolè, Federica and Ventura, Laura (2004) Robust prediction limits based on M-estimators. [Working Paper] WORKING PAPER SERIES, 8/2004 . , PADOVA (Inedito)

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Abstract (english)

In this paper we discuss a robust solution to the problem of prediction. Following Barndorff-Nielsen and Cox (1996) and Vidoni (1998), we propose improved prediction limits based on M-estimators instead of maximum likelihood estimators. To compute these robust prediction limits, the expressions of the bias and variance of an M-estimator are required. Here a general asymptotic approximation for the bias of an M-estimator is derived. Moreover, by means of comparative studies in the context of affine transformation models, we show that the proposed robust procedure for prediction behaves in a similar manner to the classical one when the model is correctly specified, but it is designed to be stable in a neighborhood of the model.

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EPrint type:Working Paper
Anno di Pubblicazione:02 July 2004
Key Words:Asymptotic expansion, Bias, Influence function, Prediction, Robustness, Scale and regression model.
Settori scientifico-disciplinari MIUR:Area 13 - Scienze economiche e statistiche > SECS-S/01 Statistica
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Statistiche
Codice ID:7045
Depositato il:02 Sep 2014 14:33
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