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A Copula Goodness-of-fit Approach Based on the Conditional Probability Integral Transform
Year Of Publication: 2007
Month Of Publication: April
Pages: 18
Download Count: 5
View Count: 1696
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 10-17-2010
Publisher: Administrator
Summary
Goodness-of-fit testing for copulae recently emerged as a challenging inferential problem and some approaches have been proposed. We investigate such an approach based on the conditional probability integral transformation. This approach implicitly weights observations at corners and edges of the unit hypercube which makes it very powerful at detecting tail heaviness for large sample sizes. However, it is shown to perform rather poor for small sample sizes. We propose a generalization that allows for any weighting, making it more robust and more powerful for small sample sizes. Another weakness is that some deviations from the null hypothesis may be neglected. We show an example and propose an extension. The original approach is shown to be a special case of our generalized and extended approach. Results from extensive Monte Carlo experiments show that the our approach keeps prescribed levels well and that certain weighting schemes produce superior power for three alternative hypotheses and for various combinations of problem dimension and sample size. The margins are treated as unknown nuisance parameters and are replaced by their
Author(s)
Berg, Daniel Sign in to follow this author
Bakken, Henrik Sign in to follow this author
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