In this paper business cycles are considered as a multivariate phenomenon and not as a univariate one determined e.g. by the GNP. The subject is to look for the number of phases of a business cycle, which can be motivated by the number of clusters in a given dataset of macro-economic variables....

Building homogenous classes is one of the main goals in clustering. Homogeneity can be measured by the intra-class variance (Bock, 1998). Especially in erosion projects but in other applications as well the separation between the built classes is as important as the homogeneity of the classes....

Statistical cluster techniques are applied in the development of two new taxonomies of manufacturing industries. The first focuses on the distinction between exogenous, location dependent comparative cost advantages, such as the relative abundance of capital or labour, and endogenously created...

Much emphasis on the sectoral perspective in economics originates in the observation of the diverse and contingent nature of competitive behaviour, where a firm's performance depends on the capability to match its organisation and strategy to the technological, social and economic restrictions...

When analyzing business cycle data, one observes that the relevant predictor variables are often highly correlated. This paper presents a method to obtain measures of importance for the classification of data in which such multicollinearity is present. In systems with highly correlated variables...

The optimization of the hyper-parameters of a statistical procedure or machine learning task is a crucial step for obtaining a minimal error. Unfortunately, the optimization of hyper-parameters usually requires many runs of the procedure and hence is very costly. A more detailed knowledge of the...

Linear Discriminant Analysis (LDA) performs well for classifica- tion of business phases even though the premises of an LDA are not met. As the variables are highly correlated there are numerical as well as interpretational shortcomings. By transforming the classification problem to a regression...