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In the last decade, simplified vine copula models have been an active area of research.
Bernstein polynomials
Lorentz, G. (1953) · 1953
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Fonctions de répartition à n dimensions et leurs marges
Sklar, A. (1959) · 1959
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A Practical Guide to Splines
de Boor, C. (1978) · 1978
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Density estimation for statistics and data analysis
Silverman, B. W. (1986) · 1986
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Stochastic Simulation
Ripley, B. D. (1987) · 1987
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Estimating the density of a copula function
Gijbels, I. and Mielniczuk, J. (1990) · 1990
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Spline Models for Observational Data
Wahba, G. (1990) · 1990
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Smoothed empirical likelihood confidence intervals for quantiles
Chen, S. X. and Hall, P. (1993) · 1993
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A semiparametric estimation procedure of dependence parameters in multivariate families of distributions
Genest, C., Ghoudi, K., and Rivest, L.-P. (1995) · 1995
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Flexible smoothing with B-splines and penalties
Eilers, P. H. C. and Marx, B. D. (1996) · 1996
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Multivariate models and dependence concepts
Joe, H. (1997) · 1997
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Smoothing parameter selection in nonparametric regression using an improved akaike information criterion
Hurvich, C. M., Simonoff, J. S., and Tsai, C.-L. (1998) · 1998
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Local regression and likelihood
Loader, C. (1999) · 1999
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Probability density decomposition for conditionally dependent random variables modeled by vines
Bedford, T. and Cooke, R. M. (2001) · 2001
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Vines — a new graphical model for dependent random variables
Bedford, T. and Cooke, R. M. (2002) · 2002
Cited alongside, same era.
Semiparametric Regression
Ruppert, D., Wand, M., and Carroll, R. (2003) · 2003
Cited alongside, same era.
The bernstein copula and its applications to modeling and approximations of multivariate distributions
Sancetta, A. and Satchell, S. (2004) · 2004
Cited alongside, same era.
The estimation of copulas: Theory and practice
Charpentier, A., Fermanian, J.-D., and Scaillet, O. (2006) · 2006
Cited alongside, same era.
Generalized additive models
Wood, S. N. (2006) · 2006
Cited alongside, same era.
Comparison of semiparametric and parametric methods for estimating copulas
Kim, G., Silvapulle, M. J., and Silvapulle, P. (2007) · 2007
Cited alongside, same era.
Selection strategies for regular vine copulae
Czado, C., Jeske, S., and Hofmann, M. (2013) · 2013
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Selecting and estimating regular vine copulae and application to financial returns
Dißmann, J., Brechmann, E. C., Czado, C., and Kurowicka, D. (2013) · 2013
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quadprog: Functions to solve Quadratic Programming Problems
Weingessel, A. (2013) · 2013
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Probit transformation for nonparametric kernel estimation of the copula density
Geenens, G., Charpentier, A., and Paindaveine, D. (2014) · 2014
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A note on the asymptotic behavior of the bernstein estimator of the copula density
Janssen, P., Swanepoel, J., and Veraverbeke, N. (2014) · 2014
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Dependence Modeling with Copulas
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Pair-copula constructions of multiple dependence
Aas, K., Czado, C., Frigessi, A., and Bakken, H. (2009) · 2009
Cited alongside, same era.
An empirical analysis of multivariate copula models
Fischer, M., Köck, C., Schlüter, S., and Weigert, F. (2009) · 2009
Cited alongside, same era.
Pair-copula constructions of multivariate copulas
Czado, C. (2010) · 2010
Cited alongside, same era.
DEPENDENCE MODELING: Vine Copula Handbook
Kurowicka, D. and Joe, H., editors (2011) · 2011
Cited alongside, same era.
About the number of vines and regular vines on n nodes
Morales-Nápoles, O., Cooke, R., and Kurowicka, D. (2011) · 2011
Cited alongside, same era.
Truncated regular vines in high dimensions with application to financial data
Brechmann, E. C., Czado, C., and Aas, K. (2012) · 2012
Cited alongside, same era.
Joe, H. (2014) · 2014
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Flexible Pair-Copula Estimation in D-vines with Penalized Splines
Kauermann, G. and Schellhase, C. (2014) · 2014
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Nonparametric estimation of pair-copula constructions with the empirical pair-copula
Haff, I. H. and Segers, J. (2015) · 2015
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Modeling and estimating multivariate dependence structures with the Bernstein copula
Rose, D. (2015) · 2015
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Simplified vine copula models: Approximations based on the simplifying assumption
Spanhel, F. and Kurz, M. S. (2015) · 2015
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Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas
Nagler, T. and Czado, C. (2016) · 2016
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Smooth nonparametric bernstein vine copulas
Scheffer, M. and Weiß, G. N. F. (2016) · 2016
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penRvine: Pair-Copula Estimation in R-Vines using Bivariate Penalized Splines
Schellhase, C. (2016) · 2016
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VineCopula: Statistical Inference of Vine Copulas
Schepsmeier, U., Stoeber, J., Brechmann, E. C., Graeler, B., Nagler, T., and Erhardt, T. (2016) · 2016
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