This paper presents a new approach to model selection based on hypothesis testing. We 4rst describe a procedure to generate di5erent scores for any candidate model from a single sample of training data and then discuss how to apply multiple comparison procedures (MCP) to model selection. MCP statistical tests allow us to compare three or more groups of data while controlling the probability of ...

An essential assumption in estimating the source parameters in electromagnetic source analysis (EMSA) is that the number of sources is known. If the incorrect number of sources is assumed in the estimation procedure, errors could occur [1]. Supek and Aine [2], for example, showed that if too many dipoles are assumed (over-modeling) then ‘spurious’ dipoles could arise with high standard errors, ...

This paper discusses a class of thresholding-based iterative selection procedures (TISP) for model selection and shrinkage. People have long before noticed the weakness of the convex l1-constraint (or the softthresholding) in wavelets and have designed many different forms of nonconvex penalties to increase model sparsity and accuracy. But for a nonorthogonal regression matrix, there is great d...