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Year 2019, , 1845 - 1858, 08.12.2019
https://doi.org/10.15672/hujms.464636

Abstract

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, , 1845 - 1858, 08.12.2019
https://doi.org/10.15672/hujms.464636

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.
There are 20 citations in total.

Details

Primary Language English
Subjects Statistics
Journal Section Statistics
Authors

Sundusit Saekaow This is me 0000-0002-5864-2685

Santi Tasena 0000-0002-7590-5993

Publication Date December 8, 2019
Published in Issue Year 2019

Cite

APA Saekaow, S., & Tasena, S. (2019). Sobolev Convergence of Empirical Bernstein Copulas. Hacettepe Journal of Mathematics and Statistics, 48(6), 1845-1858. https://doi.org/10.15672/hujms.464636
AMA Saekaow S, Tasena S. Sobolev Convergence of Empirical Bernstein Copulas. Hacettepe Journal of Mathematics and Statistics. December 2019;48(6):1845-1858. doi:10.15672/hujms.464636
Chicago Saekaow, Sundusit, and Santi Tasena. “Sobolev Convergence of Empirical Bernstein Copulas”. Hacettepe Journal of Mathematics and Statistics 48, no. 6 (December 2019): 1845-58. https://doi.org/10.15672/hujms.464636.
EndNote Saekaow S, Tasena S (December 1, 2019) Sobolev Convergence of Empirical Bernstein Copulas. Hacettepe Journal of Mathematics and Statistics 48 6 1845–1858.
IEEE S. Saekaow and S. Tasena, “Sobolev Convergence of Empirical Bernstein Copulas”, Hacettepe Journal of Mathematics and Statistics, vol. 48, no. 6, pp. 1845–1858, 2019, doi: 10.15672/hujms.464636.
ISNAD Saekaow, Sundusit - Tasena, Santi. “Sobolev Convergence of Empirical Bernstein Copulas”. Hacettepe Journal of Mathematics and Statistics 48/6 (December 2019), 1845-1858. https://doi.org/10.15672/hujms.464636.
JAMA Saekaow S, Tasena S. Sobolev Convergence of Empirical Bernstein Copulas. Hacettepe Journal of Mathematics and Statistics. 2019;48:1845–1858.
MLA Saekaow, Sundusit and Santi Tasena. “Sobolev Convergence of Empirical Bernstein Copulas”. Hacettepe Journal of Mathematics and Statistics, vol. 48, no. 6, 2019, pp. 1845-58, doi:10.15672/hujms.464636.
Vancouver Saekaow S, Tasena S. Sobolev Convergence of Empirical Bernstein Copulas. Hacettepe Journal of Mathematics and Statistics. 2019;48(6):1845-58.