Accurate forecasting of call arrivals is critical for staffing and scheduling of a telephone call center. We develop methods for interday and dynamic intraday forecasting of incoming call volumes. Our approach is to treat the intraday call volume profiles as a high-dimensional vector time...

The singular value decomposition and its interpretation as a linear biplot has proved to be a powerful tool for analysing many forms of multivariate data. Here we adapt biplot methodology to the speciffic case of compositional data consisting of positive vectors each of which is constrained to...

In order to interpret the biplot it is necessary to know which points – usually variables – are the ones that are important contributors to the solution, and this information is available separately as part of the biplot’s numerical results. We propose a new scaling of the display, called...

This study shows how correspondence analysis may be applied to a subset of response categories from a questionnaire survey (e.g., the subset of undecided responses or the subset of responses for a particular category across several questions). The idea is to maintain the original relative...

Matrix decomposition methods: Singular Value Decomposition (SVD) and Semi Discrete Decomposition (SDD) are proved to be successful in dimensionality reduction. However, to the best of our knowledge, no empirical results are presented and no comparison between these methods is done to uncover...