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Building on the work of Bedford, Cooke and Joe, we show how multivariate data, which exhibit complex patterns of dependence in the tails, can be modelled using a cascade of pair-copulae, acting on two variables at a time. We use the pair-copula decomposition of a general multivariate distribution and propose a method to perform inference. The model(More)
Due to their high flexibility, yet simple structure, pair-copula constructions (PCCs) are becoming increasingly popular for constructing continuous multivariate distributions. However, inference requires the simplifying assumption that all the pair-copulae depend on the conditioning variables merely through the two conditional distribution functions that(More)
Oslo in 1988. She is currently working as a researcher at the Norwegian Computing Center and has been involved in several projects concerning document image analysis and machine vision. Her research interests lie mainly within the various applications of statistical pattern recognition. Summary In this paper, we demonstrate that hidden Markov chains have a(More)
The problems of character recognition are today mainly due to imperfect thresholding and segmentation In this paper a new ap proach to text recognition is presented which attempts to avoid these problems by working directly on grey level images and treating an en tire word at the time The features are found from the grey levels of the image and a hidden(More)