Table of Contents:
Topic of the doctoral thesis is the theoretical investigation of methods of change-point analysis for application to telecommunication data. The models used here are motivated by models which are used in telecommunications. In particular for market share investigations related to phoned minutes linear models are appropriate. The error terms are frequently not independent as often assumed in theoretical investigations but correlated. We generalize procedures of a posteriori change-point analysis for linear models with independent errors to such allowing correlated error terms. Another important very general class of models is the model class of State Space models. State Space models are used in particular for prognoses of traffic volume in telecommunications. New procedures for a posteriori change-point analysis are developed for this model class. Concerning sequential procedures of change-point analysis we present well-known practice-oriented procedures and transfer these on linear models as well as on State Space models. Results obtained theoretically are subject of simulation studies. All programs, which are used for these, are written in the statistical programming language R. The methods examined here are applied to original data of Deutsche Telekom in an application study. This application study is not part of the thesis for data security reasons. On the one hand the conception of early warning systems is discussed, which examine observations sequentially for structural breaks (deviations from a given model). On the other hand we regard analysis systems, which examine a set of observations in retrospect (''a posteriori'') for existing change-points. The procedures supply valuable hints about structural breaks in observed data. Some of the procedures are used by Deutsche Telekom for automated monitoring of market shares as well as other characteristics.