Scientific article
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A Kolmogorov-Smirnov Type Test for Positive Quadrant Dependence

ContributorsScaillet, Olivierorcid
Publication date2005-01-01
First online date2005
Abstract

We consider a consistent test, that is similar to a Kolmogorov-Smirnov test, of the complete set of restrictions that relate to the copula representation of positive quadrant dependence. For such a test we propose and justify inference relying on a simulation based multiplier method and a bootstrap method. We also explore the finite sample behavior of both methods with Monte Carlo experiments. A first empirical illustration is given for US insurance claim data. A second one examines the presence of positive quadrant dependence in life expectancies at birth of males and females among countries.

Keywords
  • Nonparametric
  • Positive quadrant dependence
  • Copula
  • Risk management
  • Loss severity distribution
  • Bootstrap
  • Multiplier method
  • Empirical process
Citation (ISO format)
SCAILLET, Olivier. A Kolmogorov-Smirnov Type Test for Positive Quadrant Dependence. In: Canadian journal of statistics, 2005, p. 16. doi: 10.2139/ssrn.668841
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Additional URL for this publicationhttps://www.ssrn.com/abstract=668841
Journal ISSN0319-5724
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