We investigate an approach to matroid complexity that involves describing a matroid via a list of independent sets, bases, circuits, or some other family of subsets of the ground set. The computational complexity of algorithmic problems under this scheme appears to be highly dependent on the choice of input-type. We define an order on the various methods of description, and we show how this ord...

For many applications of nonlinear regression, theory does not guide the model building process by suggesting a relevant functional form. This research develops a new technique for use in this situation. Called STAT-ANN, the new method provides modelling flexibility similar to a neural network but provides a statistical basis for model selection, interpretation, and validation by following a tw...