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- W2904273786 abstract "Consider a random sample from a continuous multivariate distribution function $F$ with copula $C$. In order to test the null hypothesis that $C$ belongs to a certain parametric family, we construct an empirical process on the unit hypercube that converges weakly to a standard Wiener process under the null hypothesis. This process can therefore serve as a `tests generator' for asymptotically distribution-free goodness-of-fit testing of copula families. We also prove maximal sensitivity of this process to contiguous alternatives. Finally, we demonstrate through a Monte Carlo simulation study that our approach has excellent finite-sample performance, and we illustrate its applicability with a data analysis." @default.
- W2904273786 created "2018-12-22" @default.
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- W2904273786 date "2017-10-31" @default.
- W2904273786 modified "2023-09-23" @default.
- W2904273786 title "Goodness-of-Fit Testing for Copulas: A Distribution-Free Approach" @default.
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