A multivariate distribution possessing arbitrarily parameterized Pareto margins is formulated and studied. The distribution is believed to allow for an adequate modeling of dependent heavy tailed risks with a non-zero probability of simultaneous loss. Numerous links to certain nowadays existing...

We study a multivariate extension of the univariate exponential dispersion Tweedie family of distributions. The class, referred to as the multi-variate Tweedie family (MTwF), on the one hand includes multivariate Poisson, gamma, inverse Gaussian, stable and compound Poisson distributions and on...

A multivariate distribution possessing arbitrarily parameterized Pareto margins is formulated and studied. The distribution is believed to allow for an adequate modeling of dependent heavy tailed risks with a non-zero probability of simultaneous loss. Numerous links to certain nowadays existing...

Brown et al. (2006) derive a Stein-type inequality for the multivariate Student-t distribution. We generalize their result to the family of (multivariate) generalized hyperbolic distributions and derive a lower bound for the variance of a function of a random variable

Distributed Data Mining is the process of extracting hidden knowledge from distributed data sources. A number of DDM architectures are proposed during the last few years. Recently, Optimized Incremental Knowledge Integration Distributed Data Mining model is proposed. It is a mobile-agent based...