Goodness‐of‐fit Procedures for Copula Models Based on the Probability Integral Transformation

By Christian Genest, Jean‐François Quessy, Bruno R'emillard. 2006

460 citations recorded by the source corpus.

Subfields: Finance, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/52b85eda73e641157deec468450bc79325e52f42

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Citations in the corpus

Copula goodness-of-fit testing: an overview and power comparison (2009, methodology): “Unfortunately, the variance provided by Shih (1998) was found to be wrong by Genest et al. (2006b), where a corrected formula is provided.”
Multivariate multiparameter extreme value models and return periods: A copula approach (2010, background): “First of all, note that equation (3) represents a multivariate quantile relationship, since it corresponds to a multidimensional probability integral transform [Genest et al., 2006].”
A probabilistic framework for assessing drought recovery (2013, methodology): “…copula function is fitted from three types of single-parameter copulas, namely, Gumbel, Frank, and Clayton [Salvadori and De Michele, 2004], separately with the maximum likelihood method, and the one with the best goodness-of-fit statistic Sn [Genest et al., 2006] is selected as the final choice.”
Inference in multivariate Archimedean copula models (2011, methodology): “4 would be doomed to fail and goodness-of-fit tests based on Kn,d could not be consistent for Archimedean copula models ( Genest et al. 2006; Savu and Trede 2008).”
Goodness-of-fit tests for parametric families of Archimedean copulas (2008, methodology): “( 2006 ) and Wang and Wells ( 2000 ) propose tests based on Kendall's process of Barbe et al .”
Comparison of semiparametric and parametric methods for estimating copulas (2007, methodology): “The p-values for the goodness of fit test statistic, Sn, of Genest et al. (2006) computed by the bootstrap method outlined in Section 4.2 therein, are also given in Table 7.”
FAST LARGE-SAMPLE GOODNESS-OF-FIT TESTS FOR COPULAS (2011, unknown): “For some large integer N , repeat the following steps for every k ∈ {1, . . . , N}: (a) Generate n i.i.d. random variates Z(k)1 , . . . , Z (k) n with expectation 0 and variance 1.”
Modeling Multivariate Distributions with Continuous Margins Using the copula R Package (2010, methodology): “Following Genest et al. (2006), we restrict ourselves to the 1466 uncensored claims.”
Multivariate non-normally distributed random variables in climate research - introduction to the copula approach (2008, background): “Especially copula speciﬁc tests are just emerging (Genest et al., 2006).”