The paper considers the problem of selecting one of two not necessarily nested competing regression models based on comparative evaluations of their abilities in each of two different issues: The first pertains to viewing the problem as a “best-fitting” model determination problem in the...

In this paper, an evaluation method is suggested for selecting one of two competing models based on certain predictive ability ratings. The main focus is on the case of linear models that are not necessarily nested. In the context of such models, the test procedure is based on a sample statistic...

The paper discusses extensions of the well-known hypergeometric and negative hypergeometric distributions for describing data with multiple counts. The derivation of these extensions is based on certain urn schemes that allow for sampling clusters of items rather than individual items. The...