Robust model selection procedures are introduced as a robust modification of the Akaike information criterion (AIC) and Mallows Cp. These extensions are based on the weighted likelihood methodology. When the model is correctly specified, these robust criteria are asymptotically equivalent to the...

We propose a one-step estimator for the vector of regression and error-scale parameters in a linear regression model. The estimator is asymptotically normal and fully efficient. Given appropriate initial values it achieves very low bias and high breakdown point.

In these notes we show that the Pearson residuals (PR) [Lindsay, B.G., 1994. Efficiency versus robustness: the case for minimum Hellinger distance and related methods. Ann. Statist. 22, 1018-1114.] have a natural asymptotic lower bound under the gross error model which can be used in the problem...

This paper studies the ability of the k -factor GARMA processes to model and forecast the volatility of an intraday financial time series. Forecasting results from the k -factor GARMA model are obtained and compared with those produced by a conventional SARIMA model.

In this paper, in order to investigate if a long memory model will provide good forecasts even if the real DGP is affected by level shifts (as suggested by Diebold, F.X., Inoue, A., 2001. Long memory and regime switching Journal of Econometrics, 105, 131-159) we compare via simulations the...