The development of sensor networks has enabled detailed tracking of customer behavior in stores. Shopping path data which records each customer’s position and time information is attracting attention as new marketing data. However, there are no proposed marketing models which can identify good...

This paper presents a flexible scan test statistic to detect disease clusters in data sets represented as a hierarchical tree. The algorithm searches through the branches of the tree and it is able to aggregate leaves located in different branches. The test statistic combines two terms, the...

The purpose of this paper is to analyze the current temporal and spatial trajectories in nanotechnology research in order to display the worldwide patterns of scientific domains across main geo-economic players. Current trends of nanotechnology have been growing in chemistry and medicine because...

This paper demonstrates the hazard of “stir-fry” regressions, which are used extensively in financial research to produce desirable results by reporting only one or a small number of regressions out of the tens or hundreds that are typically estimated. It is shown, by using data on the...

The use of linear and log-linear models for scorecard construction is nearly universal. In this paper we address the question of non-linearity in the distribution of a scorecard’s inferred log-odds to score relationship. Linear scorecards are excellent and robust ranking tools, but the...

We propose a one-norm support vector machine (SVM) formulation as an alternative to the well-known formulation that uses parameter C in order to balance the two inherent objective functions of the problem. Our formulation is motivated by the ϵ-constraint approach that is used in bicriteria...

This paper examines the inflation “pass-through” problem in American monetary policy, defined as the relationship between changes in the growth rates of individual goods and the subsequent economy-wide rate of growth of consumer prices. Initial relationships are established with Granger...