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A kolmogorov-smirnov type test for positive quadrant dependence

ContributorsScaillet, Olivierorcid
Published inCanadian journal of statistics, vol. 33, no. 3, p. 415-427
Publication date2005
Abstract

The author considers a consistent, Kolmogorov-Smirnov type of test of the complete set of restrictions that relate to the copula representation of positive quadrant dependence. For such a test, he proposes and justifies inference relying on a simulation-based multiplier method and a bootstrap method. He also explores the finite-sample behaviour of both methods with Monte Carlo experiments. A first empirical illustration is given for American insurance claim data. A second one examines the presence of positive quadrant dependence in life expectancies at birth of males and females across countries.

Keywords
  • Bootstrap
  • Copula
  • Empirical process
  • Loss severity distribution
  • Multiplier method
  • Nonparametric estimator
  • Positive quadrant dependence
  • Risk management
Citation (ISO format)
SCAILLET, Olivier. A kolmogorov-smirnov type test for positive quadrant dependence. In: Canadian journal of statistics, 2005, vol. 33, n° 3, p. 415–427. doi: 10.1002/cjs.5540330307
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Article (Accepted version)
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ISSN of the journal0319-5724
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