Paper shows that, under assumption that the single forecasts which enter the combination are unbiased, imposing some constraints on coordinates of <em>M </em>-estimator (of corresponding regression coefficients) leads to a gain in the asymptotic variance of one-step forward prediction evaluated by means...

This article considers a wide class of censoring problems and presents a construction rule for an objective function. This objective function generalises the orginary likelihood as well as particular "likelihoods" used for estimation in several censoring models. Under regularity conditions the...

This paper studies an alternative bias correction for the M-estimator, which is obtained by correcting the moment equation in the spirit of Firth (1993). In particular, this paper compares the stochastic expansions of the analytically bias-corrected estimator and the alternative estimator and...

Most dimension reduction methods based on nonparametric smoothing are highly sensitive to outliers and to data coming from heavy-tailed distributions. We show that the recently proposed methods by Xia et al. (2002) can be made robust in such a way that preserves all advantages of the original...

In this paper, we study M-estimation for the partially linear model under monotonic constraints. We use monotone B-splines to approximate the monotone nonparametric function. We show the large sample properties of the resulting estimators. The proposed estimator of parameter part is root-n...

This paper studies robust inference in unit root and cointegration models. The analysis covers a range of important inference problems including testing stationarity against unit roots, testing for structure change in nonstationary regressions, and testing for cointegration. We analyze these...