This paper studies model selection for a general class of models based on minimizing random distance functions. The proposed model selection criteria are consistent, regardless of whether models are nested or nonnested and regardless of whether models are correctly specified or not, in the sense that they select the best model with the least number of parameters with probability converging to 1...