 One possible response to the piecemeal confirmation problems discussed here is to turn to a Bayesian framework for confirmation, but similar problems arise here for nonlinear models. Given that there are no perfect models in the model class to which we would apply a Bayesian scheme and given the fact that imperfect models will fail to reproduce or predict target system behavior over time scales that may be short compared to our interests, there again is no guarantee that monotonic improvement can be achieved for our nonlinear models (I leave aside the problem that having no perfect model in our model class renders many Bayesian confirmation schemes ill-defined). 