In many applications it is required to segment a time series into its locally stationary parts. Two applications are presented: As a first example consider online monitoring of a BTA Deep-Hole-Drilling process. Here chattering and spiralling of the drilling tool should be avoided by process...

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...

We use Dynamic Bayesian networks to classify business cycle phases. We compare classifiers generated by learning the Dynamic Bayesian network structure on different sets of admissible network structures. Included are sets of network structures of the Tree Augmented Naive Bayes (TAN) classifiers...

We propose a new information theoretically based optimization criterion for the estimation of mixture density models and compare it with other methods based on maximum likelihood and maximum a posterio estimation. For the optimization, we employ an evolutionary algorithm which estimates both...

This paper presents a model of resource extraction based on two of its key aspects: investment and taxation. A mining firm is considered which may be in an environment of perfect competition or have a monopoly. It plans to extract from a fixed stock of resources. Before extraction begins, the...