Year 2019,
Volume: 48 Issue: 6, 1845 - 1858, 08.12.2019
Sundusit Saekaow
Santi Tasena
References
- [1] J. Behboodian, A. Dolati, and M. Úbeda-Flores. A multivariate version of gini’s rank
association coefficient. Statist. Papers, 48(2):295–304, 2007.
- [2] N. Blomqvist. On a measure of dependence between two random variables. Ann.
Math. Statist., 21(4):593–600, 1950.
- [3] H. Dette, K. F. Siburg, and P. A. Stoimenov. A copula-based non-parametric measure
of regression dependence. Scand. J. Stat., 40(1):21–41, 2013.
- [4] S. Gaißer, M. Ruppert, and F. Schmid. A multivariate version of hoeffding’s phisquare.
J. Multivariate Anal., 101(10):2571–2586, 2010.
- [5] W. Hoeffding. The collected works of Wassily Hoeffding. Springer-Verlag, 1994.
- [6] P. Janssen, J. Swanepoel, and N. Veraverbeke. Large sample behavior of the bernstein
copula estimator. J. Statist. Plann. Inference, 142(5):1189 – 1197, 2012.
- [7] H. Joe. Multivariate concordance. J. Multivariate Anal., 35(1):12–30, 1990.
- [8] M. G. Kendall. A new measure of rank correlation. Biometrika, 30(1/2):81–93, 1938.
- [9] H. O. Lancaster. Measures and indeces of dependence. In M. Kotz and N. L. Johnson,
editors, Encyclopedia of Statistical Sciences, volume 2, pages 334–339. Wiley, New
York, 1982.
- [10] R. B. Nelsen. Nonparametric measures of multivariate association. Lecture Notes-
Monograph Series, 28:223–232, 1996.
- [11] A. Rényi. On measures of dependence. Acta Math. Hungar., 10(3):441–451, 1959.
- [12] F. Schmid, R. Schmidt, T. Blumentritt, S. Gaißer, and M. Ruppert. Copula-based
measures of multivariate association. In P. Jaworski, F. Durante, W. K. Härdle, and
T. Rychlik, editors, Copula Theory and Its Applications, volume 198 of Lecture Notes
in Statistics – Proceedings, pages 209–236. Springer Berlin Heidelberg, 2010.
- [13] B. Schweizer and E. F. Wolff. On nonparametric measures of dependence for random
variables. Ann. Statist., 9(4):879–885, 1981.
- [14] K. F. Siburg and P. A. Stoimenov. A measure of mutual complete dependence.
Metrika, 71:239–251, 2010.
- [15] A. Sklar. Fonctions de répartition á n dimensions et leurs marges. Publ. Inst. Statist.
Univ. Paris, 8:229–231, 1959.
- [16] M. Taylor. Bernstein Polynomials and n-Copulas. ArXiv e-prints, March 2009.
- [17] M. D. Taylor. Multivariate measures of concordance. Ann. Inst. Statist. Math.,
59(4):789–806, 2006.
- [18] W. Trutsching. On a strong metric on the space of copulas and its induced dependence
measure. J. Math. Anal. Appl., 384:690–705, 2011.
- [19] M. Úbeda-Flores. Multivariate versions of blomqvist’s beta and spearman’s footrule.
Ann. Inst. Statist. Math., 57(4):781–788, 2005.
- [20] E. F. Wolff. N-dimensional measures of dependence. Stochastica, 4(3):175–188, 1980.
Sobolev Convergence of Empirical Bernstein Copulas
Year 2019,
Volume: 48 Issue: 6, 1845 - 1858, 08.12.2019
Sundusit Saekaow
Santi Tasena
Abstract
In this work, we prove that Bernstein estimator always converges to the true copula under Sobolev distances. The rate of convergences is provided in case the true copula has bounded second order derivatives. Simulation study has also been done for Clayton copulas. We then use this estimator to estimate measures of complete dependence for weather data. The result suggests a nonlinear relationship between the dust density in Chiang Mai, Thailand and the temperature and the humidity level.
References
- [1] J. Behboodian, A. Dolati, and M. Úbeda-Flores. A multivariate version of gini’s rank
association coefficient. Statist. Papers, 48(2):295–304, 2007.
- [2] N. Blomqvist. On a measure of dependence between two random variables. Ann.
Math. Statist., 21(4):593–600, 1950.
- [3] H. Dette, K. F. Siburg, and P. A. Stoimenov. A copula-based non-parametric measure
of regression dependence. Scand. J. Stat., 40(1):21–41, 2013.
- [4] S. Gaißer, M. Ruppert, and F. Schmid. A multivariate version of hoeffding’s phisquare.
J. Multivariate Anal., 101(10):2571–2586, 2010.
- [5] W. Hoeffding. The collected works of Wassily Hoeffding. Springer-Verlag, 1994.
- [6] P. Janssen, J. Swanepoel, and N. Veraverbeke. Large sample behavior of the bernstein
copula estimator. J. Statist. Plann. Inference, 142(5):1189 – 1197, 2012.
- [7] H. Joe. Multivariate concordance. J. Multivariate Anal., 35(1):12–30, 1990.
- [8] M. G. Kendall. A new measure of rank correlation. Biometrika, 30(1/2):81–93, 1938.
- [9] H. O. Lancaster. Measures and indeces of dependence. In M. Kotz and N. L. Johnson,
editors, Encyclopedia of Statistical Sciences, volume 2, pages 334–339. Wiley, New
York, 1982.
- [10] R. B. Nelsen. Nonparametric measures of multivariate association. Lecture Notes-
Monograph Series, 28:223–232, 1996.
- [11] A. Rényi. On measures of dependence. Acta Math. Hungar., 10(3):441–451, 1959.
- [12] F. Schmid, R. Schmidt, T. Blumentritt, S. Gaißer, and M. Ruppert. Copula-based
measures of multivariate association. In P. Jaworski, F. Durante, W. K. Härdle, and
T. Rychlik, editors, Copula Theory and Its Applications, volume 198 of Lecture Notes
in Statistics – Proceedings, pages 209–236. Springer Berlin Heidelberg, 2010.
- [13] B. Schweizer and E. F. Wolff. On nonparametric measures of dependence for random
variables. Ann. Statist., 9(4):879–885, 1981.
- [14] K. F. Siburg and P. A. Stoimenov. A measure of mutual complete dependence.
Metrika, 71:239–251, 2010.
- [15] A. Sklar. Fonctions de répartition á n dimensions et leurs marges. Publ. Inst. Statist.
Univ. Paris, 8:229–231, 1959.
- [16] M. Taylor. Bernstein Polynomials and n-Copulas. ArXiv e-prints, March 2009.
- [17] M. D. Taylor. Multivariate measures of concordance. Ann. Inst. Statist. Math.,
59(4):789–806, 2006.
- [18] W. Trutsching. On a strong metric on the space of copulas and its induced dependence
measure. J. Math. Anal. Appl., 384:690–705, 2011.
- [19] M. Úbeda-Flores. Multivariate versions of blomqvist’s beta and spearman’s footrule.
Ann. Inst. Statist. Math., 57(4):781–788, 2005.
- [20] E. F. Wolff. N-dimensional measures of dependence. Stochastica, 4(3):175–188, 1980.