Univariate and multivariate Pareto models

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• 作者：Barry C Arnold
• 关键词：Inequality ; Heavy tails ; Generalized Pareto ; Feller ; Pareto ; Kumaraswamy distribution ; Hidden truncation ; Conditional specification
• 刊名：Journal of Statistical Distributions and Applications
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：1
• 期：1
• 全文大小：257KB
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• 作者单位：Barry C Arnold (10)
  
  10. Department of Statistics, University of California, Riverside, USA
  
• 刊物类别：Statistical Theory and Methods; Statistics and Computing/Statistics Programs; Science, general;
• 刊物主题：Statistical Theory and Methods; Statistics and Computing/Statistics Programs; Science, general;
• 出版者：Springer Berlin Heidelberg
• ISSN：2195-5832

文摘

The Pareto distribution has long been recognized as a suitable model for many non-negative socio-economic variables. Univariate and multivariate variations abound. Some unification is possible by representing the Pareto variables in terms of independent gamma distributed components. Further unification is sometimes possible since some of the frequently used multivariate Pareto models share the same copula. In some cases, inference strategies can be developed to take advantage of the stochastic representations in terms of gamma components. Keywords Inequality Heavy tails Generalized Pareto Feller-Pareto Kumaraswamy distribution Hidden truncation Conditional specification