THE BERNSTEIN COPULA AND ITS APPLICATIONS TO MODELING AND APPROXIMATIONS OF MULTIVARIATE DISTRIBUTIONS

By Alessio Sancetta, Stephen E. Satchell. Econometric Theory, 2004

287 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/93a5f743833debdcc2628f623b035a6b0f651f03

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Citations in the corpus

Dependence modeling in non-life insurance using the Bernstein copula (2012, methodology): “URL: http://www.uni-ulm.de/mawi/ivw (S.D. Marek). may serve as a model for an unknown underlying dependence structure (Sancetta and Satchell, 2004).”
Non-parametric copulas for circular–linear and circular–circular data: an application to wind directions (2013, methodology): “The objective of this article is to show how circular– linear and circular–circular distributions can be constructed via empirical Bernstein copula functions, see e.g. Sancetta and Satchell (2004).”
Copula-Based Models for Financial Time Series (2009, background): “The key complication introduced when applying Sklar’s theorem to conditional distributions is that the conditioning set, Ft−1, must be the same for all marginal distributions and the copula. Fermanian and Wegkamp (2004) and Fermanian and Scaillet (2005) consider the implications of a failure to use ”
Copula-Based Measures of Multivariate Association (2010, methodology): “Sancetta and Satchell [90] proposed using the density of the empirical Bernstein copula as this estimator is itself a copula density; it is given in Bouezmarni et.”
Flexible Copula Density Estimation with Penalized Hierarchical B‐splines (2013, methodology): “Furthermore, we fit the data with Bernstein polynomials as basis functions but without any penalization (see Sancetta & Satchell, 2004).”
COPULA-BASED CHARACTERIZATIONS FOR HIGHER ORDER MARKOV PROCESSES (2009, methodology): “as in Sancetta and Satchell (2004) , Hermite polynomials as in Gram-Charlier copulas discussed in Ibragimov (2005a), or Fourier polynomials similar to the constructions discussed in Section 5.7 The”
Copula Methods for Forecasting Multivariate Time Series (2013, background): “Related articles include Genest and Rivest (1993) and Capéraà, et al. (1997) for iid data, and Fermanian and Scaillet (2003), Fermanian, et al. (2004), Sancetta and Satchell (2004) and Ibragimov (2009) for time series data. empirical illustration.”
A review of copula models for economic time series (2012, background): “[55], Sancetta and Satchell [132] and Ibragimov [95].”
Using Copulas to Construct Bivariate Foreign Exchange Distributions with an Application to the Sterling Exchange Rate Index (2005, unknown): “Ultimately this leads us to choose a very flexible representation in the form of a Bernstein expansion, as developed recently by Sancetta (2003) and Sancetta and Satchell (2004).”
Quantile Selection Models with an Application to Understanding Changes in Wage Inequality (2017, unknown): “[61] Sancetta,A.”
Nonparametric estimation of simplified vine copula models: comparison of methods (2017, background): “Based on this idea, the Bernstein copula density was de ned in [32].”
Copulas in Econometrics (2014, background): “The majority of the literature considers parametric copula models (for nonparametric estimation of copulas, see Genest & Rivest 1993 and Capéraà et al. 1997 for i.i.d. data and Fermanian & Scaillet 2003, Fermanian et al. 2004, Sancetta & Satchell 2004, and Ibragimov 2009 for time series data).”