Empirical Processes Based on Pseudo-observations 11: The Multivariate Case

By Kilani Ghoudi. 2004

54 citations recorded by the source corpus.

Subfields: Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/3403af6e349876b9ef6a2214273d1176e93778ce

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In Management Science and Operations Research

Citations in the corpus

Goodness‐of‐fit Procedures for Copula Models Based on the Probability Integral Transformation (2006, methodology): “It follows from example 3.2.1 of Ghoudi & Rémillard (2004) that provided that ch is smooth enough hypothesis III is automatically verified when hypotheses I and II hold, so that proposition 1 then holds under hypotheses I, II and IV only.”
Empirical processes indexed by estimated functions (2007, methodology): “…5.1 and 5.3 for indicator functions involve non-trivial restrictions on the underlying distribution η0 of the data, while the results for indexing by Lipschitz functions given in Corollaries 5.2 and 5.4 involve almost no restrictions on η0 (but significantly smoother indexing functions θ).”
A note on bootstrap approximations for the empirical copula process (2010, unknown): “The asymptotic behavior of Cn was studied in several papers, including Gänssler and Stute (1987), Ghoudi and Rémillard (2004) or Tsukahara (2005) among others.”
Goodness-of-Fit Tests for Copulas of Multivariate Time Series (2017, unknown): “As argued in Genest et al. [33] and Ghoudi and Rémillard [35], these tests should be avoided.”
Copula Methods for Forecasting Multivariate Time Series (2013, methodology): “Method of moments-type estimators, where the parameter of a given family of copulas has a known, invertible, mapping to a dependence measure (such as rank correlation or Kendall s tau) are considered in Genest (1987), Ghoudi and Rémillard (2004) and Rémillard (2010), among others.”
Asymptotics of empirical copula processes under non-restrictive smoothness assumptions (2010, background): “(3.7) In ( ∞([0,1]d))2, we have by Lemma A.1 in Rémillard and Scaillet [24], (αn,α ′ n) (α,α′) (n → ∞), (3.8) where α′ is an independent copy of α.”
Semiparametric estimation in copula models (2005, result): “A similar result was proved in Fermanian, RaduloviC & Wegkamp (2004) and Ghoudi & RCmillard (2004), using different conditions.”
A generalized framework for deriving nonparametric standardized drought indicators (2015, methodology): “There are also alternative methods for deriving joint empirical probabilities such as the Kendall s [20,31,53] that can be used for deriving nonparametric multivariate indicators based on multiple variables (e.”
A review of copula models for economic time series (2012, unknown): “Method of moments-type estimators, where the parameter of a given family of copulas has a known, invertible, mapping to a dependence measure (such as rank correlation or Kendall’s tau) are considered in [64,75,125,68], among others.”