A Kolmogorov-Smirnov type test for positive quadrant dependence

被引:73
作者
Scaillet, O
机构
[1] Univ Geneva, HEC Geneve, CH-1211 Geneva, Switzerland
[2] Univ Geneva, FAME, CH-1211 Geneva, Switzerland
来源
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 2005年 / 33卷 / 03期
关键词
bootstrap; copula; empirical process; loss severity distribution; multiplier method; nonparametric estimator; positive quadrant dependence; risk management;
D O I
10.1002/cjs.5540330307
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The author considers a consistent, Kolmogorov-Smimov 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.
引用
收藏
页码:415 / 427
页数:13
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