Filter methods are used to promote convergence of Newton methods for constrainted optimization problems. A filter accepts Newton steps that either decrease the objective function or reduce the violation of the constraints. We briefly review the basic concepts underlying filter methods, and then present a new nonmonotone or shadow filter.