Bayesian copula selection
Tài liệu tham khảo
Bagdonavicius, 1999, Characterizations and semiparametric regression estimation in Archimedean copulas, J. Appl. Statist. Sci., 8, 137
Bouyé, E., Durrleman, A., Nikeghbali, A., Riboulet, G., Roncalli, T., 2000. Copulas for finance—a reading guide and some applications. Technical Report, Groupe de Recherche Opérationnelle, Crédit Lyonnais.
Bretthorst, G.L., 1996. An introduction to model selection using probability theory as logic. In: Heidbreger, G. (Ed.), Maximum Entropy and Bayesian Methods, pp. 1–42.
Chen, 2005, Pseudo-likelihood ratio tests for semiparametric multivariate copula model selection, La Revue Canadienne de Statistique, 33, 389, 10.1002/cjs.5540330306
Chen, X., Fan, Y., Patton, A., 2003. Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates. Discussion Paper 483, Financial Markets Group, International Asset Management.
Cherubini, 2004
Deheuvels, P., 1979. La fonction de dépendance empirique et ses propriétés. Un test non paramétrique d’indépendance. Académie Royale de Belgique, Bulletin de la Classe des Sciences, 5ème Série 65, pp. 274–292.
De Michele, 2003, A generalized Pareto intensity-duration model of storm rainfall exploiting 2-copulas, J. Geophys. Res., 108, 10.1029/2002JD002534
Dobrić, J., Schmidt, F., 2004. Testing goodness of fit for parametric families of copulas—application to financial data. Seminar of economic and social statistics, University of Cologne.
Durrleman, V., Nikeghbali, A., Roncalli, T., 2000. Which copula is the right one? Working document, Groupe de Recherche Opérationnelle, Crédit Lyonnais.
Embrechts, P., McNeil, A., Straumann, D., 2002. Correlation and dependence in risk management: properties and pitfalls. Risk Management: Value at Risk and Beyond. Cambridge University Press, Cambridge, pp. 176–223.
Embrechts, P., Lindskog, F., McNeil, A., 2003. Modelling dependence with copulas and applications to risk management. Handbook of Heavy Tailed Distributions in Finance. Elsevier, Amsterdam, pp. 329–384.
Evin, G., 2004. Choix de la meilleure famille de copule en hydrologie. Internship Report, École Nationale de la Statistique et de l’Analyse de l’Information.
Favre, 2004, Multivariate hydrological frequency analysis using copulas, Water Resources Res., 40
Fermanian, 2005, Goodness-of-fit tests for copulas, J. Multivariate Anal., 95, 119, 10.1016/j.jmva.2004.07.004
Frahm, 2003, Elliptical copulas: applicability and limitations, Statist. Probab. Lett., 63, 275, 10.1016/S0167-7152(03)00092-0
Frees, 1998, Understanding relationships using copulas, North American Actuarial J., 2, 1, 10.1080/10920277.1998.10595667
Genest, 1986, The joy of copulas: bivariate distributions with uniform marginals, Amer. Statist., 40, 280, 10.2307/2684602
Genest, 1993, Statistical inference procedures for bivariate Archimedean copulas, J. Amer. Statist. Assoc., 88, 1034, 10.2307/2290796
Genest, 2005, Locally most powerful rank tests of independence for copulas models, J. Nonparametric Statist., 17, 521, 10.1080/10485250500038926
Genest, C., Quessy, J.-F., Rémillard, B., 2005a. Local efficiency of a Cramér–von Mises test of independence. J. Multivariate Anal., in press.
Genest, C., Quessy, J.-F., Rémillard, B, 2005b. Goodness-of-fit procedures for copula models based on the probability integral transformation. Scand. J. Statist., 32, in press.
Jaynes, 2003
Joe, 1997
Juri, 2003, Tail dependence from a distributional point of view, Extremes, 6, 213, 10.1023/B:EXTR.0000031180.93684.85
Justel, 1997, A multivariate Kolmogorov–Smirnov test of goodness of fit, Statist. Probab. Lett., 35, 251, 10.1016/S0167-7152(97)00020-5
Kass, 1996, The selection of prior distributions by formal rules, J. Amer. Statist. Assoc., 91, 1343, 10.2307/2291752
Kendall, M., Stuart, A., 1983. The Advanced Theory of Statistics, fourth ed., vol. 2. Oxford University Press, New York.
Kruskal, 1958, Ordinal measures of association, J. Amer. Statist. Assoc., 53, 814, 10.2307/2281954
Nelsen, 1999, 10.1007/978-1-4757-3076-0
Pollard, 1979, General chi-square goodness-of-fit tests with data-dependent cells, Z. Wahrscheinlichkeitstheorie und verwandte Gebiete, 50, 317, 10.1007/BF00534153
Rosenblatt, 1952, Remarks on a multivariate transformation, Ann. Math. Statist., 23, 470, 10.1214/aoms/1177729394
Saïd, M., 2004. Méthodes statistiques pour tester la dépendance entre les variables latentes pour des risques concurrents. Ph.D. Thesis, Université Laval.
Schmidt, 2002, Tail dependence for elliptically contoured distributions, Math. Meth. Oper. Res., 55, 301, 10.1007/s001860200191
Sklar, A., 1959. Fonctions de répartition à n dimensions et leurs marges. Publications de l’Institut de Statistique de l’Université de Paris 8, pp. 229–231.
Whelan, 2004, Sampling from Archimedean copulas, Quantitative Finance, 4, 339, 10.1088/1469-7688/4/3/009