In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

This paper develops a statistical model of wealth distribution that imposes no parametric structure on the fluctuations of household wealth. In this general setting, we use new techniques to obtain a closed-form household-by-household characterization of the stable distribution of wealth and...

Variable selection methods and model selection approaches are valuable statistical tools that are indispensable for almost any statistical modeling question. This review first considers the use of information criteria for model selection. Such criteria provide an ordering of the considered...