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Considering results obtained in
magnetic levitation and suspension of the symmetrical bodies are designed and
developed several experiments of the electromagnetism that demonstrate the
effects of a superconductor necessary to the magnetic levitation/suspension.
This generates bases to the development of a reactor to impulse and anti-gravitational
magnetic displacement of a vehicle considering the production and transference
of Eddy currents on their structure to microscopic level and the effect of
auto-levitation/auto-suspension that is obtained with the iso-rotations of the
impulse magnetic ring of the proper vehicle.
In this article, we present a new family of estimators for the regression parameter β in the Additive Hazards Model which represents a gain in robustness not only against outliers but also against unspecific contamination schemes. They are consistent and asymptotically normal and furthermore, and they have a nonzero breakdown point. In Survival Analysis, the Additive Hazards Model proposes a hazard function of the form , where ？is a common nonparametric baseline hazard function and z is a vector of independent variables. For this model, the seminal work of Lin and Ying (1994) develops an estimator for the regression parameter β which is asymptotically normal and highly efficient. However, a potential drawback of that classical estimator is that it is very sensitive to outliers. In an attempt to gain robustness, álvarez and Ferrarrio (2013) introduced a family of estimators for β which were still highly efficient and asymptotically normal, but they also had bounded influence functions. Those estimators, which are developed using classical Counting Processes methodology, still retain the drawback of having a zero breakdown point.