General Trimmed Estimation: Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaced by DP 2007-65)

High breakdown-point regression estimators protect against large errors and data con- tamination. Motivated by some { the least trimmed squares and maximum trimmed like- lihood estimators { we propose a general trimmed estimator, which uni¯es and extends many existing robust procedures. We derive here the consistency and asymptotic distri- bution of the proposed general trimmed estimator under mild ¯-mixing conditions and demonstrate its applicability in nonlinear regression, time series, and limited dependent variable models.