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A kolmogorov-smirnov type test for positive quadrant dependence

Contributors

Scaillet, Olivier

Published in

Canadian journal of statistics, vol. 33, no. 3, p. 415-427

Publication date

2005

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

UNIGE affiliation entities

UNIGE research groups

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

Main files (1)

Article (Accepted version)

Identifiers

Journal ISSN

0319-5724
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676downloads

Technical informations

Creation

14/01/2016 16:51:00

First validation

14/01/2016 16:51:00

Update

15/03/2023 00:05:00

Status update

15/03/2023 00:04:59

Last indexation

31/10/2024 02:34:34
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