by a substantial amount of outliers. Tests based on a comparison of local medians standardized by a highly robust …

Standard median filters preserve abrupt shifts (edges) and remove impulsive noise (outliers) from a constant signal but … much more vulnerable to outliers. Application of robust regression methods, in particular of the repeated median, has been … suggested for removing subsequent outliers from a signal with trends. A fast algorithm for updating the repeated median in …

The paper derives an algorithm for computing leave-k-out diagnostics for the detection of patches of outliers for …

observations. As detection and removal of outliers in high dimension is much more difficult than in one dimension, we propose an M … type marginal integration estimator that automatically corrects the extreme influence of outliers. We establish the …

. We find that when outliers (especially China) are removed, the trust-growth relationship is no longer robust. On average …

uncertainty, we use Least Trimmed Squares, a robust estimation technique, to identify outliers and investigate how they affect the … the sample than previously claimed, and that outliers affect the results. Nevertheless trust seems quite important …

resistant to patches of additive outliers. The data span two samples of 5 years ranging from 1986 to 1995. Using asymptotic … arguments and Monte Carlo simulations, in which we evaluate our empirical method, we show that patches of outliers can have …