We propose a computer intensive method for linear dimension reduction which minimizes the classification error directly. Simulated annealing (Bohachevsky et al 1986) as a modern optimization technique is used to solve this problem effectively. This approach easily allows to incorporate user...

Thirteen Stylized Facts of the german economy are studied with different descriptive statistical methods. The results of this study are considered with respect to other results from Project B3 Multivariate Bestimmung und Untersuchung von Konjunkturzyklen.

We present a descriptive analysis of stylized facts for the German business cycle. We demonstrate that simple ad-hoc instructions for identifying univariate rules characterizing the German business cycle 1955-1994 lead to an error rate comparable to standard multivariate methods.

In this paper, we examine the German business cycle (from 1955 to 1994) in order to identify univariate and multivariate outliers as well as influence points corresponding to Linear Discriminant Analysis. The locations of the corresponding observations are compared and economically interpreted.

In order to replace the univariate indicators standard in the literature (cp. [Opp96]) by a multivariate representation of business cycles, the relevant 'stylized facts' are to be identified which optimally characterize the development of business cycle phases. Based on statistical...

We propose a standardized partition space (SPS) that offers a unifying framework for the comparison of a wide variety of classification rules. Using SPS, one can define measures for the performance of classifiers w.r.t. goodness concepts beyond the expected rate of correct classifications of the...

In this paper a projection pursuit method is developed which determines optimal multivariate latent factor models based on a flexible loss function. This way, the unknown model coefficients are estimated with respect to optimal predictive power. The specification of the loss function in...