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T-Convolution and its applications to n-dimensional distributions
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Published/Copyright:
January 22, 2010
Abstract
In this paper we introduce the notion of T-convolution, which is a generalization of convolution to higher dimensions. By using T-convolution we construct n-dimensional distributions having n + 1 axes of symmetry. In addition, we can generalize well-known symmetric probability distributions in one dimension to higher dimensions. In particular, we consider generalizations of Laplace and triangle continuous distributions and we show their plots in the two-dimensional case. As an example of discrete distributions, we study the T-convolution of Poisson distributions in the plane.
Received: 2009-04-02
Published Online: 2010-01-22
Published in Print: 2009-December
© de Gruyter 2009
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- Asymptotic properties of random matrices of long-range percolation model
- T-Convolution and its applications to n-dimensional distributions
- Some procedures for extending random operators
- Common random fixed points for multivalued random operators without S- and T-weakly commuting random operators
- Fractional SPDEs with non-Lipschitz coefficients
Articles in the same Issue
- Asymptotic properties of random matrices of long-range percolation model
- T-Convolution and its applications to n-dimensional distributions
- Some procedures for extending random operators
- Common random fixed points for multivalued random operators without S- and T-weakly commuting random operators
- Fractional SPDEs with non-Lipschitz coefficients
