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A bivariate distribution with Lomax and geometric margins
Authors:Marek Arendarczyk  Tomasz J Kozubowski  Anna K Panorska
Institution:1. Mathematical Institute, University of Wroc?aw, pl. Grunwaldzki 2/4, 50-384 Wroc?aw, Poland;2. Department of Mathematics & Statistics, University of Nevada, Reno, NV 89557, USA
Abstract:We develop a stochastic model describing the joint distribution of (X,N), where N has a geometric distribution while X is the sum of N dependent, heavy-tail Pareto components. Models of this form arise in many applications, ranging from hydro-climatology to finance and insurance. We present fundamental properties of this vector, including marginal and conditional distributions, moments, representations, and parameter estimation. We also include an example from finance, illustrating modeling potential of this new bivariate distribution.
Keywords:primary  60E05  secondary  60G50  62E15  62F10  62H05  62H12  62P05  BEG model  Dependence by mixing  Distribution theory  Financial data  Mixed distribution  Maximum likelihood estimation  Multivariate pareto distribution  Random sum
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