We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Copula structure analysis.
- Authors
Klüppelberg, Claudia; Kuhn, Gabriel
- Abstract
We extend the standard approach of correlation structure analysis for dimension reduction of high dimensional statistical data. The classical assumption of a linear model for the distribution of a random vector is replaced by the weaker assumption of a model for the copula. For elliptical copulas a correlation-like structure remains, but different margins and non-existence of moments are possible. After introducing the new concept and deriving some theoretical results we observe in a simulation study the performance of the estimators: the theoretical asymptotic behaviour of the statistics can be observed even for small sample sizes. Finally, we show our method at work for a financial data set and explain differences between our copula-based approach and the classical approach. Our new method yielear models also.
- Subjects
STATISTICS; LINEAR statistical models; LINEAR dependence (Mathematics); EQUATIONS; STATISTICAL correlation; MATRICES (Mathematics)
- Publication
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2009, Vol 71, Issue 3, p737
- ISSN
1369-7412
- Publication type
Article
- DOI
10.1111/j.1467-9868.2009.00707.x