R. Abraham, J. Delmas, and H. Guo, Critical Multi-type Galton???Watson Trees Conditioned to be Large, Journal of Theoretical Probability, vol.2, issue.2, 2015.
DOI : 10.1007/s10959-016-0707-3
URL : https://hal.archives-ouvertes.fr/hal-01224696

M. Abramowitz and I. A. Stegun, Handbook of mathematical functions: with formulas, graphs, and mathematical tables, 1970.

I. S. Abramson, On bandwidth variation in kernel estimates-a square root law. The Annals of Statistics, pp.1217-1223, 1982.

A. Aghakouchak, Entropy???Copula in Hydrology and Climatology, Journal of Hydrometeorology, vol.15, issue.6, pp.2176-2189, 2014.
DOI : 10.1175/JHM-D-13-0207.1

B. C. Arnold, N. Balakrishnan, and H. N. Nagaraja, A first course in order statistics, Siam, vol.54, 1992.
DOI : 10.1137/1.9780898719062

P. Asghari, V. Fakoor, and M. Sarmad, A Berry-Esseen Type Bound in Kernel Density Estimation for a Random Left-Truncation Model, Communications for Statistical Applications and Methods, vol.21, issue.2, pp.115-124, 2014.
DOI : 10.5351/CSAM.2014.21.2.115

O. Asserin, A. Loredo, M. Petelet, and B. Iooss, Global sensitivity analysis in welding simulations -what are the material data you really need? Finite Elements in Analysis and Design, pp.1004-1016, 2011.

J. Audibert, Progressive mixture rules are deviation suboptimal, Advances in Neural Information Processing Systems, pp.41-48, 2008.

J. Avérous, C. Genest, and S. C. Kochar, On the dependence structure of order statistics, Journal of Multivariate Analysis, vol.94, issue.1, pp.159-171, 2005.
DOI : 10.1016/j.jmva.2004.03.004

A. Barron, L. Birgé, and P. Massart, Risk bounds for model selection via penalization. Probability theory and related fields, pp.301-413, 1999.

A. R. Barron and T. M. Cover, Minimum complexity density estimation. Information Theory, IEEE Transactions on, vol.37, issue.4, pp.1034-1054, 1991.
DOI : 10.1109/18.86996

A. R. Barron and C. Sheu, Approximation of Density Functions by Sequences of Exponential Families, The Annals of Statistics, vol.19, issue.3, pp.1347-1369, 1991.
DOI : 10.1214/aos/1176348252

A. R. Barron, L. Gyorfi, and E. C. Van-der-meulen, Distribution estimation consistent in total variation and in two types of information divergence. Information Theory, IEEE Transactions on, vol.38, issue.5, pp.1437-1454, 1992.

M. S. Bartlett, Statistical estimation of density functions. Sankhy¯ a: The Indian Journal of Statistics, Series A, pp.245-254, 1963.

M. Baudin, A. Dutfoy, B. Iooss, and A. Popelin, Open TURNS: An industrial software for uncertainty quantification in simulation. arXiv preprint, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01107849

T. Bedford and K. Wilson, On the construction of minimum information bivariate copula families, Annals of the Institute of Statistical Mathematics, vol.26, issue.4, pp.1-21, 2013.
DOI : 10.1007/s10463-013-0422-0

P. Bellec, Optimal exponential bounds for aggregation of density estimators. arXiv preprint, 2014.

O. Benrabah, E. O. Saïd, and A. Tatachak, A kernel mode estimate under random left truncation and time series model: asymptotic normality, Statistical Papers, vol.24, issue.396, pp.887-910, 2014.
DOI : 10.1007/s00362-014-0613-7

K. Bertin, Asymptotically exact minimax estimation in sup-norm for anisotropic H??lder classes, Bernoulli, vol.10, issue.5, pp.873-888, 2004.
DOI : 10.3150/bj/1099579160

S. Bertino, Sulla dissomiglianza tra mutabili cicliche. Metron, pp.53-88, 1977.

P. J. Bickel, Some contributions to the theory of order statistics, Proc. Fifth Berkeley Sympos, pp.575-591, 1965.

J. Bigot, R. B. Lirio, J. Loubes, and L. M. Alvarez, Adaptive estimation of spectral densities via wavelet thresholding and information projection. arXiv preprint, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00440424

L. Birgé, P. Massart-for-lucien-le, and C. , From Model Selection to Adaptive Estimation, Festschrift, pp.55-87978, 1997.
DOI : 10.1007/978-1-4612-1880-7_4

P. J. Boland, M. Hollander, K. Joag-dev, and S. Kochar, Bivariate Dependence Properties of Order Statistics, Journal of Multivariate Analysis, vol.56, issue.1, pp.75-89, 1996.
DOI : 10.1006/jmva.1996.0005

J. Borwein, A. Lewis, and R. Nussbaum, Entropy Minimization, DAD Problems, and Doubly Stochastic Kernels, Journal of Functional Analysis, vol.123, issue.2, pp.264-307, 1994.
DOI : 10.1006/jfan.1994.1089
URL : http://doi.org/10.1006/jfan.1994.1089

S. Boyd and L. Vandenberghe, Convex optimization, 2004.

R. C. Bradley, On positive spectral density functions, Bernoulli, vol.8, issue.2, pp.175-193, 2002.

L. Breiman, W. Meisel, and E. Purcell, Variable Kernel Estimates of Multivariate Densities, Technometrics, vol.21, issue.6, pp.135-144, 1977.
DOI : 10.1214/aoms/1177704472

F. Bunea, A. B. Tsybakov, and M. H. Wegkamp, Aggregation for Gaussian regression, The Annals of Statistics, vol.35, issue.4
DOI : 10.1214/009053606000001587
URL : http://arxiv.org/abs/0710.3654

C. Butucea, Exact adaptive pointwise estimation on Sobolev classes of densities, ESAIM: Probability and Statistics, vol.5, pp.1-31, 2001.
DOI : 10.1051/ps:2001100

C. Butucea, J. Delmas, A. Dutfoy, and R. Fischer, Modélisation de la dépendance sous contrainte déterministe, Proceedings of Congrès Lambda Mu 19 de Maîtrise des Risques et Sûreté de Fonctionnement, pp.10-4267, 2014.

C. Butucea, J. Delmas, A. Dutfoy, and R. Fischer, Copule d'entropie maximale avec des statistiques d'ordre fixées, Proceedings of Journées de Statistiques Rennes, 2014.

C. Butucea, J. Delmas, A. Dutfoy, and R. Fischer, Maximum entropy copula with given diagonal section, Journal of Multivariate Analysis, vol.137, pp.61-81, 2015.
DOI : 10.1016/j.jmva.2015.01.003
URL : http://arxiv.org/abs/1312.5219

C. Butucea, J. Delmas, A. Dutfoy, and R. Fischer, Nonparametric estimation of distributions of order statistics with application to nuclear engineering, Safety and Reliability of Complex Engineered Systems: ESREL 2015, 2015.
DOI : 10.1201/b19094-348

C. Butucea, J. Delmas, A. Dutfoy, and R. Fischer, Estimation rapide non-paramétrique de la densité de la distribution d'entropie maximale pour les statistiques d'ordre, Proceedings of Journées de Statistiques Rennes, 2015.

C. Butucea, J. Delmas, A. Dutfoy, and R. Fischer, Maximum entropy distribution of order statistics with given marginals, 2015.

C. Butucea, J. Delmas, A. Dutfoy, and R. Fischer, Fast adaptive estimation of log-additive exponential models in kullback-leibler divergence. arXiv preprint, 2016.

C. Butucea, J. Delmas, A. Dutfoy, and R. Fischer, Optimal exponential bounds for aggregation of estimators for the kullback-leibler loss. arXiv preprint, 2016.

T. Cacoullos, Estimation of a multivariate density, Annals of the Institute of Statistical Mathematics, vol.27, issue.1, pp.179-189, 1966.
DOI : 10.1007/BF02869528

O. Catoni, The mixture approach to universal model selection, École Normale Supérieure. Citeseer, 1997.

O. Catoni, Universal aggregation rules with exact bias bounds, 1999.

N. Cencov, Estimation of an unknown density function from observations, In Dokl. Akad. Nauk, SSSR, vol.147, pp.45-48, 1962.

C. Chang and D. Politis, Aggregation of spectral density estimators, Statistics & Probability Letters, vol.94, pp.204-213, 2014.
DOI : 10.1016/j.spl.2014.07.017

E. Chicken and T. T. Cai, Block thresholding for density estimation: local and global adaptivity, Journal of Multivariate Analysis, vol.95, issue.1, pp.76-106, 2005.
DOI : 10.1016/j.jmva.2004.07.003

Y. Chow, S. Geman, and L. Wu, Consistent cross-validated density estimation. The Annals of Statistics, pp.25-38, 1983.
DOI : 10.1214/aos/1176346053

B. Chu, Recovering copulas from limited information and an application to asset allocation, Journal of Banking & Finance, vol.35, issue.7, pp.1824-1842, 2011.
DOI : 10.1016/j.jbankfin.2010.12.011

B. R. Crain, An Information Theoretic Approach to Approximating a Probability Distribution, SIAM Journal on Applied Mathematics, vol.32, issue.2, pp.339-346, 1977.
DOI : 10.1137/0132027

I. Csiszár, $I$-Divergence Geometry of Probability Distributions and Minimization Problems, The Annals of Probability, vol.3, issue.1
DOI : 10.1214/aop/1176996454

I. Cuculescu and R. Theodorescu, Copulas: diagonals, tracks. Revue roumaine de mathématiques pures et appliquées, pp.731-742, 2001.

D. Dai, P. Rigollet, and T. Zhang, Deviation optimal learning using greedy $Q$-aggregation, The Annals of Statistics, vol.40, issue.3
DOI : 10.1214/12-AOS1025
URL : http://arxiv.org/abs/1203.2507

A. S. Dalalyan and J. Salmon, Sharp oracle inequalities for aggregation of affine estimators, The Annals of Statistics, vol.40, issue.4
DOI : 10.1214/12-AOS1038SUPP
URL : https://hal.archives-ouvertes.fr/hal-00587225

A. S. Dalalyan and A. B. Tsybakov, Aggregation by Exponential Weighting and Sharp Oracle Inequalities, Learning theory, pp.97-111, 2007.
DOI : 10.1007/978-3-540-72927-3_9
URL : https://hal.archives-ouvertes.fr/hal-00160857

A. S. Dalalyan and A. B. Tsybakov, Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity, Machine Learning, pp.39-61, 2008.
DOI : 10.1007/s10994-008-5051-0
URL : https://hal.archives-ouvertes.fr/hal-00291504

H. A. David and H. N. Nagaraja, Order statistics, 1970.
DOI : 10.1002/0471722162

R. B. Davies, Asymptotic inference in stationary Gaussian time-series, Advances in Applied Probability, vol.15, issue.03, pp.469-497, 1973.
DOI : 10.2307/1905674

E. De-amo, M. D. Carrillo, and J. F. Sánchez, Absolutely continuous copulas with given sub-diagonal section. Fuzzy Sets and Systems, pp.105-113, 2013.

E. De-amo, H. D. Meyer, M. D. Carrillo, and J. F. Sánchez, Characterization of copulas with given diagonal and opposite diagonal sections. Fuzzy Sets and Systems, Theme: Uncertainty and Copulas, pp.63-77, 2016.

B. V. De-melo, M. A. Mendes, and . Sanfins, The limiting copula of the two largest order statistics of independent and identically distributed samples, Brazilian Journal of Probability and Statistics, vol.21, pp.85-101, 2007.

G. F. De-montricher, R. A. Tapia, and J. R. Thompson, Nonparametric maximum likelihood estimation of probability densities by penalty function methods. The Annals of Statistics, pp.1329-1348, 1975.

M. A. Dempster, E. A. Medova, and S. W. Yang, EMPIRICAL COPULAS FOR CDO TRANCHE PRICING USING RELATIVE ENTROPY, International Journal of Theoretical and Applied Finance, vol.62, issue.04, pp.679-701, 2007.
DOI : 10.1090/S0025-5718-1970-0274029-X

L. Depradeux, Simulation numérique du soudage-acier 316L: validation sur cas tests de complexité croissante, 2004.

D. Devroye, J. Beirlant, R. Cao, R. Fraiman, P. Hall et al., Universal smoothing factor selection in density estimation: theory and practice, Test, vol.52, issue.1, pp.223-320, 1997.
DOI : 10.1007/BF02564701

E. , D. Nezza, G. Palatucci, and E. Valdinoci, Hitchhiker's guide to the fractional Sobolev spaces, Bull. Sci. Math, vol.136, issue.5, pp.521-573

D. L. Donoho, I. M. Johnstone, G. Kerkyacharian, and D. Picard, Density estimation by wavelet thresholding. The Annals of Statistics, pp.508-539, 1996.
DOI : 10.1214/aos/1032894451
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.41.8824

D. Dubhashi and O. Häggström, A Note on Conditioning and Stochastic Domination for Order Statistics, Journal of Applied Probability, vol.34, issue.02, pp.575-579, 2008.
DOI : 10.1017/S0305004100034241

C. F. Dunkl and Y. Xu, Orthogonal polynomials of several variables, 2001.

F. Durante and P. Jaworski, Absolutely continuous copulas with given diagonal sections Communications in Statistics -Theory and Methods, pp.2924-2942, 2008.

F. Durante, R. Mesiar, and C. Sempi, On a family of copulas constructed from the diagonal section. Soft Computing, pp.490-494, 2006.

F. Durante, A. Kolesárová, R. Mesiar, and C. Sempi, COPULAS WITH GIVEN DIAGONAL SECTIONS: NOVEL CONSTRUCTIONS AND APPLICATIONS, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol.41, issue.04, pp.397-410, 2007.
DOI : 10.1006/jmva.1993.1061

F. Durante, J. F. Sánchez, and W. Trutschnig, Multivariate copulas with hairpin support, Journal of Multivariate Analysis, vol.130, pp.323-334, 2014.
DOI : 10.1016/j.jmva.2014.06.009

F. Durante, J. Fernández-sánchez, and R. Pappadà, Copulas, diagonals, and tail dependence . Fuzzy Sets and Systems, pp.22-41, 2015.
DOI : 10.1016/j.fss.2014.03.014

F. Durante, J. Fernández-sánchez, J. J. Quesada-molina, and M. Ú. Flores, Diagonal plane sections of trivariate copulas, Information Sciences, vol.333, pp.81-87, 2016.
DOI : 10.1016/j.ins.2015.11.024

S. Y. Efroimovich, Nonparametric estimation of a density of unknown smoothness. Theory of Probability & Its Applications, pp.557-568, 1986.

V. A. Epanechnikov, Non-parametric estimation of a multivariate probability density. Theory of Probability and Its Applications, pp.153-158, 1969.

A. Erdely and J. M. González-barrios, On the Construction of Families of Absolutely Continuous Copulas with Given Restrictions, Communications in Statistics - Theory and Methods, vol.12, issue.4, pp.4-6649, 2006.
DOI : 10.1080/03610929608831791

A. Erdely, J. M. González-barrios, and M. M. Hernández-cedillo, Frank's condition for multivariate archimedean copulas. Fuzzy Sets and Systems, pp.131-136, 2014.
DOI : 10.1016/j.fss.2013.05.017

G. Fredricks and R. Nelsen, Copulas Constructed from Diagonal Sections, Distributions with given Marginals and Moment Problems, pp.129-136978, 1997.
DOI : 10.1007/978-94-011-5532-8_16

D. Freedman and P. Diaconis, On the histogram as a density estimator: L 2 theory. Probability Theory and Related Fields, pp.453-476, 1981.

D. Freedman and P. Diaconis, On the maximum deviation between the histogram and the underlying density, Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete, pp.139-167, 1981.
DOI : 10.1007/BF00531558

T. Gasser, H. Muller, and V. Mammitzsch, Kernels for nonparametric curve estimation, Journal of the Royal Statistical Society. Series B (Methodological), pp.238-252, 1985.

E. Giné and R. Nickl, An exponential inequality for the distribution function of the kernel density estimator, with applications to adaptive estimation. Probability Theory and Related Fields, pp.569-596, 2008.

A. Goldenshluger and O. Lepski, Bandwidth selection in kernel density estimation: Oracle inequalities and adaptive minimax optimality, The Annals of Statistics, vol.39, issue.3, pp.1608-1632, 2011.
DOI : 10.1214/11-AOS883
URL : https://hal.archives-ouvertes.fr/hal-01265258

A. Goldenshluger and O. Lepski, On adaptive minimax density estimation on R d . Probability Theory and Related Fields, pp.479-543, 2014.
DOI : 10.1007/s00440-013-0512-1
URL : https://hal.archives-ouvertes.fr/hal-01265245

G. K. Golubev, Nonparametric estimation of smooth densities of a distribution in L 2, Problemy Peredachi Informatsii, vol.28, issue.1, pp.52-62, 1992.

I. J. Good, Maximum entropy for hypothesis formulation, especially for multidimensional contingency tables. The Annals of Mathematical Statistics, pp.911-934, 1963.

O. Grothe, J. Schnieders, and J. Segers, Measuring association and dependence between random vectors, Journal of Multivariate Analysis, vol.123, pp.96-110, 2014.
DOI : 10.1016/j.jmva.2013.08.019

E. Guerre, I. Perrigne, and Q. Vuong, Optimal Nonparametric Estimation of First-price Auctions, Econometrica, vol.68, issue.3, pp.525-574, 2000.
DOI : 10.1111/1468-0262.00123

P. Hall, Estimating a density on the positive half line by the method of orthogonal series, Annals of the Institute of Statistical Mathematics, vol.34, issue.1, pp.351-362, 1980.
DOI : 10.1007/BF02480339

P. Hall, On Trigonometric Series Estimates of Densities, The Annals of Statistics, vol.9, issue.3, pp.683-685, 1981.
DOI : 10.1214/aos/1176345474

P. Hall, Comparison of two orthogonal series methods of estimating a density and its derivatives on an interval, Journal of Multivariate Analysis, vol.12, issue.3, pp.432-449, 1982.
DOI : 10.1016/0047-259X(82)90076-8

P. Hall, On Kullback-Leibler loss and density estimation. The Annals of Statistics, pp.1491-1519, 1987.
DOI : 10.1214/aos/1176350606

P. Hall and J. Marron, On the amount of noise inherent in bandwidth selection for a kernel density estimator. The Annals of Statistics, pp.163-181, 1987.

P. Hall, G. Kerkyacharian, and D. Picard, Block threshold rules for curve estimation using kernel and wavelet methods, The Annals of Statistics, vol.26, issue.3, pp.922-942, 1998.
DOI : 10.1214/aos/1024691082

Z. Hao and V. Singh, Entropy-copula method for single-site monthly streamflow simulation, Water Resources Research, vol.47, issue.1, p.2012
DOI : 10.1029/2009WR008388

T. Herbst, An application of randomly truncated data models in reserving IBNR claims, Insurance: Mathematics and Economics, vol.25, issue.2, pp.123-131, 1999.
DOI : 10.1016/S0167-6687(99)00028-1

T. Hu and H. Chen, Dependence properties of order statistics, Journal of Statistical Planning and Inference, vol.138, issue.7, pp.2214-2222, 2008.
DOI : 10.1016/j.jspi.2007.09.013

A. J. Izenman, Review Papers: Recent Developments in Nonparametric Density Estimation, Journal of the American Statistical Association, vol.11, issue.413, pp.205-224, 1991.
DOI : 10.1080/01621459.1985.10478217

K. D. Jarman and P. D. Whitney, Integrating correlated bayesian networks using maximum entropy, Applied Mathematical Sciences, vol.5, issue.48, pp.2361-2371, 2011.

P. Jaworski, On copulas and their diagonals, Information Sciences, vol.179, issue.17, pp.2863-2871, 2009.
DOI : 10.1016/j.ins.2008.09.006

P. Jaworski and T. Rychlik, On distributions of order statistics for absolutely continuous copulas with applications to reliability, Kybernetika, vol.44, issue.6, pp.757-776, 2008.

E. T. Jaynes, Information Theory and Statistical Mechanics, Physical Review, vol.106, issue.4, p.620, 1957.
DOI : 10.1103/PhysRev.106.620

H. Joe, Multivariate models and dependence concepts, volume 73 of Monographs on Statistics and Applied Probability, 1997.

P. Joly, D. Commenges, and L. Letenneur, A Penalized Likelihood Approach for Arbitrarily Censored and Truncated Data: Application to Age-Specific Incidence of Dementia, Biometrics, vol.54, issue.1, pp.185-194, 1998.
DOI : 10.2307/2534006
URL : https://hal.archives-ouvertes.fr/inserm-00182453

A. Juditsky and A. Nemirovski, Functional aggregation for nonparametric regression

A. Juditsky, P. Rigollet, and A. B. Tsybakov, Learning by mirror averaging, The Annals of Statistics, vol.36, issue.5, pp.2183-2206, 2008.
DOI : 10.1214/07-AOS546
URL : https://hal.archives-ouvertes.fr/hal-00341026

G. Kerkyacharian and D. Picard, Density estimation in Besov spaces, Statistics & Probability Letters, vol.13, issue.1, pp.15-24, 1992.
DOI : 10.1016/0167-7152(92)90231-S

G. Kerkyacharian and D. Picard, Density estimation by kernel and wavelets methods: Optimality of besov spaces Statistics and Probability Letters, pp.327-336, 1993.

G. Kerkyacharian, D. Picard, and K. Tribouley, L p Adaptive Density Estimation, Bernoulli, vol.2, issue.3, pp.229-247, 1996.
DOI : 10.2307/3318521

G. Kerkyacharian, O. Lepski, and D. Picard, Nonlinear estimation in anisotropic multiindex denoising. Probability theory and related fields, pp.137-170, 2001.

J. M. Keynes, A treatise on probability, Courier Corporation, 2013.
DOI : 10.1007/978-1-349-00843-8

S. Kim and H. David, On the dependence structure of order statistics and concomitants of order statistics, Journal of Statistical Planning and Inference, vol.24, issue.3, pp.363-368, 1990.
DOI : 10.1016/0378-3758(90)90055-Y

J. P. Klein and M. L. Moeschberger, Survival analysis: techniques for censored and truncated data, 2005.
DOI : 10.1007/978-1-4757-2728-9

J. Koo and W. Kim, Wavelet density estimation by approximation of log-densities, Statistics & Probability Letters, vol.26, issue.3, pp.271-278, 1996.
DOI : 10.1016/0167-7152(95)00020-8

S. Kullback and R. A. Leibler, On Information and Sufficiency, The Annals of Mathematical Statistics, vol.22, issue.1, pp.79-86, 1951.
DOI : 10.1214/aoms/1177729694

S. W. Lagakos, L. Barraj, and V. De-gruttola, Nonparametric analysis of truncated survival data, with application to AIDS, Biometrika, vol.75, issue.3, pp.515-523, 1988.
DOI : 10.1093/biomet/75.3.515

R. Lebrun and A. Dutfoy, Copulas for order statistics with prescribed margins, Journal of Multivariate Analysis, vol.128, pp.120-133, 2014.
DOI : 10.1016/j.jmva.2014.03.006

G. Lecué, Lower bounds and aggregation in density estimation, The Journal of Machine Learning Research, vol.7, pp.971-981, 2006.

G. Lecué and S. Mendelson, Aggregation via empirical risk minimization. Probability Theory and Related Fields, pp.591-613, 2009.

O. Lepski, Multivariate density estimation under sup-norm loss: Oracle approach, adaptation and independence structure, The Annals of Statistics, vol.41, issue.2, pp.1005-1034, 2013.
DOI : 10.1214/13-AOS1109
URL : https://hal.archives-ouvertes.fr/hal-01265250

O. V. Lepski, A problem of adaptive estimation in gaussian white noise. Teoriya Veroyatnostei i ee Primeneniya, pp.459-470, 1990.

O. V. Lepskii, Asymptotically minimax adaptive estimation. i: Upper bounds. optimally adaptive estimates. Theory of Probability & Its Applications, pp.682-697, 1992.
DOI : 10.1137/1136085

X. Luo and W. Tsai, Nonparametric estimation of bivariate distribution under right truncation with application to panic disorder, Journal of Statistical Planning and Inference, vol.139, issue.4, pp.1559-1568, 2009.
DOI : 10.1016/j.jspi.2008.08.017

D. Lynden-bell, A Method of Allowing for Known Observational Selection in Small Samples Applied to 3CR Quasars, Monthly Notices of the Royal Astronomical Society, vol.155, issue.1, pp.95-118, 1971.
DOI : 10.1093/mnras/155.1.95

J. S. Marron and D. Nolan, Canonical kernels for density estimation, Statistics & Probability Letters, vol.7, issue.3, pp.195-199, 1988.
DOI : 10.1016/0167-7152(88)90050-8

A. Meeuwissen and T. Bedford, Minimally informative distributions with given rank correlation for use in uncertainty analysis, Journal of Statistical Computation and Simulation, vol.79, issue.1-4, pp.143-174, 1997.
DOI : 10.1016/0377-2217(92)90149-4

C. C. Moore, The Degree of Randomness in a Stationary Time Series, The Annals of Mathematical Statistics, vol.34, issue.4, pp.1253-1258, 1963.
DOI : 10.1214/aoms/1177703860

J. Navarro and N. Balakrishnan, Study of some measures of dependence between order statistics and systems, Journal of Multivariate Analysis, vol.101, issue.1, pp.52-67, 2010.
DOI : 10.1016/j.jmva.2009.04.016

J. Navarro and F. Spizzichino, On the relationships between copulas of order statistics and marginal distributions, Statistics & Probability Letters, vol.80, issue.5-6, pp.473-479, 2010.
DOI : 10.1016/j.spl.2009.11.025
URL : https://hal.archives-ouvertes.fr/hal-00612019

R. B. Nelsen, An introduction to copulas Springer Series in Statistics, 2006.

R. B. Nelsen, J. J. Molina, J. A. Lallena, and M. Ú. Flores, Best-possible bounds on sets of bivariate distribution functions, Journal of Multivariate Analysis, vol.90, issue.2, pp.348-358, 2004.
DOI : 10.1016/j.jmva.2003.09.002

R. B. Nelsen, J. J. Quesada-molina, J. A. Rodríguez-lallena, and M. Ú. Flores, On the construction of copulas and quasi-copulas with given diagonal sections, Insurance: Mathematics and Economics, vol.42, issue.2, pp.473-483, 2008.
DOI : 10.1016/j.insmatheco.2006.11.011

A. Nemirovski, Topics in non-parametric statistics. Ecole d'Eté de Probabilités de Saint- Flour, p.85, 2000.

E. Parzen, On estimation of a probability density function and mode. The Annals of Mathematical Statistics, pp.1065-1076, 1962.

A. Pasanisi, Uncertainty analysis and decision-aid: methodological, technical and managerial contributions to engineering and R&D studies, 2014.
URL : https://hal.archives-ouvertes.fr/tel-01002915

A. Pasanisi and A. Dutfoy, An Industrial Viewpoint on Uncertainty Quantification in Simulation: Stakes, Methods, Tools, Examples, Uncertainty Quantification in Scientific Computing, pp.27-45, 2012.
DOI : 10.1007/978-3-642-32677-6_3
URL : https://hal.archives-ouvertes.fr/hal-01518664

E. Pasha and S. Mansoury, Determination of maximum entropy multivariate probability distribution under some constraints, Applied Mathematical Sciences, vol.2, issue.57, pp.2843-2849, 2008.

M. Petelet, B. Iooss, O. Asserin, and A. Loredo, Latin hypercube sampling with inequality constraints AStA Advances in Statistical Analysis, pp.325-339, 2010.

J. Piantadosi, P. Howlett, and J. Borwein, Copulas with maximum entropy. Optimization Letters, pp.99-125, 2012.
DOI : 10.1007/s11590-010-0254-2

J. Piantadosi, P. Howlett, J. Borwein, and J. Henstridge, Maximum entropy methods for generating simulated rainfall. Numerical Algebra, Control and Optimization, pp.233-256
DOI : 10.3934/naco.2012.2.233
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.226.3389

H. Poincaré, Calcul des probabilités. Les Grands Classiques Gauthier-Villars. [Gauthier- Villars Great Classics, Éditions Jacques Gabay, 1912.

A. Popelin, A. Balmont, J. Clement, and J. Angles, Sensitivity analysis of a welding thermomechanical simulation model, Proceedings of the 12th Annual Conference of the European Network for Business and Industrial Statistics, 2012.

A. Popelin, A. Balmont, J. Clement, and J. Angles, Sensitivity analysis of a numerical welding simulation model, Proceedings of the 21ème Congrès Français de Mécanique, 2042.

D. Pougaza, A. Mohammad-djafari, and J. Bercher, Link between copula and tomography, Pattern Recognition Letters, vol.31, issue.14, pp.312258-2264, 2010.
DOI : 10.1016/j.patrec.2010.05.001
URL : https://hal.archives-ouvertes.fr/hal-00509705

J. J. Quesada-molina, S. Saminger-platz, and C. Sempi, Quasi-copulas with a given subdiagonal section Nonlinear Analysis: Theory, Methods & Applications, pp.4654-4673, 2008.

E. Remy, A. Popelin, and A. Feng, Modelling dependence using copulas -an implementation in the field of structural reliability

P. Rigollet, Kullback?Leibler aggregation and misspecified generalized linear models. The Annals of Statistics, pp.639-665, 2012.
DOI : 10.1214/11-aos961
URL : http://arxiv.org/abs/0911.2919

P. Rigollet and A. B. Tsybakov, Linear and convex aggregation of density estimators, Mathematical Methods of Statistics, vol.16, issue.3, pp.260-280, 2007.
DOI : 10.3103/S1066530707030052
URL : https://hal.archives-ouvertes.fr/hal-00204675

M. Rosenblatt, Remarks on a Multivariate Transformation, The Annals of Mathematical Statistics, vol.23, issue.3, pp.470-472
DOI : 10.1214/aoms/1177729394

M. Rosenblatt, Remarks on Some Nonparametric Estimates of a Density Function, The Annals of Mathematical Statistics, vol.27, issue.3, pp.832-837, 1956.
DOI : 10.1214/aoms/1177728190

L. Rüschendorf and W. Thomsen, Note on the Schrödinger equation and I-projections

T. Rychlik, Distributions and expectations of order statistics for possibly dependent random variables, Journal of Multivariate Analysis, vol.48, issue.1, pp.31-42, 1994.
DOI : 10.1016/0047-259X(94)80003-E

A. Samarov and A. Tsybakov, Aggregation of density estimators and dimension reduction Advances in statistical modeling and inference, Essays in honor of Kjell A. Doksum, pp.233-251, 2007.

V. Schmitz, Revealing the dependence structure between X(1) and X(n), Journal of Statistical Planning and Inference, vol.123, issue.1, pp.41-47, 2004.
DOI : 10.1016/S0378-3758(03)00143-5

P. J. Schönbucher, Credit Derivatives pricing models: models, pricing, and implementation, 2003.

S. C. Schwartz, Estimation of Probability Density by an Orthogonal Series, The Annals of Mathematical Statistics, vol.38, issue.4, pp.1261-1265, 1177698795.
DOI : 10.1214/aoms/1177698795

D. W. Scott, On optimal and data-based histograms, Biometrika, vol.66, issue.3, pp.605-610, 1979.
DOI : 10.1093/biomet/66.3.605
URL : http://biomet.oxfordjournals.org/cgi/content/short/66/3/605

D. W. Scott and G. R. Terrell, Biased and Unbiased Cross-Validation in Density Estimation, Journal of the American Statistical Association, vol.9, issue.400, pp.1131-1146, 1987.
DOI : 10.1214/aoms/1177696810

C. E. Shannon, A Mathematical Theory of Communication, Bell System Technical Journal, vol.27, issue.3, pp.379-423, 1948.
DOI : 10.1002/j.1538-7305.1948.tb01338.x

M. Sklar, Fonctions de répartition à n dimensions et leurs marges, Publ. Inst. Statist. Univ. Paris, vol.8, pp.229-231, 1959.

E. Strzalkowska-kominiak and W. Stute, On the probability of holes in truncated samples, Journal of Statistical Planning and Inference, vol.140, issue.6, pp.1519-1528, 2010.
DOI : 10.1016/j.jspi.2009.12.017

E. A. Sungur and Y. Yang, Diagonal copulas of archimedean class, Communications in Statistics - Theory and Methods, vol.8, issue.403, pp.1659-1676, 1996.
DOI : 10.1080/03610919008812920

G. R. Terrell and D. W. Scott, Variable Kernel Density Estimation, The Annals of Statistics, vol.20, issue.3, pp.1236-1265, 1176348768.
DOI : 10.1214/aos/1176348768

R. C. Tolman, The principles of statistical mechanics [167] A. Tsybakov Aggregation and high-dimensional statistics. Lecture notes for the course given at the École d'été de Probabilités in Saint-Flour, 1938.

A. B. Tsybakov, Optimal Rates of Aggregation, Learning Theory and Kernel Machines, pp.303-313, 2003.
DOI : 10.1007/978-3-540-45167-9_23
URL : https://hal.archives-ouvertes.fr/hal-00104867

A. B. Tsybakov, Introduction to nonparametric estimation, 2008.
DOI : 10.1007/b13794

B. W. Turnbull, The empirical distribution function with arbitrarily grouped, censored and truncated data, J. Roy. Statist. Soc. Ser. B, vol.38, issue.3, pp.290-295, 1976.

T. Wagner, Nonparametric estimates of probability densities, IEEE Transactions on Information Theory, vol.21, issue.4, pp.438-440, 1975.
DOI : 10.1109/TIT.1975.1055408

G. Wahba, Optimal Convergence Properties of Variable Knot, Kernel, and Orthogonal Series Methods for Density Estimation, The Annals of Statistics, vol.3, issue.1, pp.15-29
DOI : 10.1214/aos/1176342997

G. G. Walter, Approximation of the delta function by wavelets, Journal of Approximation Theory, vol.71, issue.3, pp.329-343, 1992.
DOI : 10.1016/0021-9045(92)90123-6

M. Wegkamp, Model selection in nonparametric regression, The Annals of Statistics, vol.31, issue.1, pp.252-273, 2003.
DOI : 10.1214/aos/1046294464

M. H. Wegkamp, Quasi-universal bandwidth selection for kernel density estimators, Canadian Journal of Statistics, vol.12, issue.2, pp.409-420, 1999.
DOI : 10.2307/3315649

X. Wu, Calculation of maximum entropy densities with application to income distribution, Journal of Econometrics, vol.115, issue.2, pp.347-354, 2003.
DOI : 10.1016/S0304-4076(03)00114-3

X. Wu, Exponential Series Estimator of multivariate densities, Journal of Econometrics, vol.156, issue.2, pp.354-366, 2010.
DOI : 10.1016/j.jeconom.2009.11.005

Y. Yang, Combining Different Procedures for Adaptive Regression, Journal of Multivariate Analysis, vol.74, issue.1, pp.135-161, 2000.
DOI : 10.1006/jmva.1999.1884
URL : http://doi.org/10.1006/jmva.1999.1884

Y. Yang, Mixing strategies for density estimation. The Annals of Statistics, pp.75-87, 2000.
DOI : 10.1214/aos/1016120365
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.40.9039

Y. Yang, Aggregating regression procedures to improve performance, Bernoulli, vol.10, issue.1, pp.25-47, 2004.
DOI : 10.3150/bj/1077544602

Y. Yang and A. Barron, Information-theoretic determination of minimax rates of convergence . The Annals of Statistics, pp.1564-1599, 1999.

T. Zhang, From ?-entropy to kl-entropy: Analysis of minimum information complexity density estimation. The Annals of Statistics, pp.2180-2210, 2006.

N. Zhao and W. T. Lin, A copula entropy approach to correlation measurement at the country level, Applied Mathematics and Computation, vol.218, issue.2, pp.628-642, 2011.
DOI : 10.1016/j.amc.2011.05.115