Search
Menu
All issues Volume 6 (2023) 4open, 6 (2023) 2 References
Issue
4open
Volume 6, 2023
Statistical Inference in Markov Processes and Copula Models
Article Number 2
Number of page(s) 7
Section Mathematics - Applied Mathematics
DOI https://doi.org/10.1051/fopen/2023001
Published online 14 February 2023
  1. de Finetti B (1929), Funzione caratteristica di un fenomeno aleatorio, in Atti del Congresso Inter nazionale dei Matematici: Bologna del 3 al 10 de settembre di 1928, Vol. 6 (Comunicazioni, sezione IV (A)-V-VII), pp. 179–190. [Google Scholar]
  2. Hewitt E, Savage LJ (1955), Symmetric measures on Cartesian products. Trans Am Math Soc 80, 2, 470–501. https://doi.org/10.2307/1992999. [CrossRef] [Google Scholar]
  3. Aldous DJ (1985), Exchangeability and related topics, in: P.L. Hennequin (Ed.), École d'Été de Probabilités de Saint-Flour XIII – 1983, Vol. 1117, Lecture Notes in Mathematics, Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0099421. [Google Scholar]
  4. Mai J-F (2020), The infinite extendibility problem for exchangeable real-valued random vectors. Probab Surv 17, 677–753. https://doi.org/10.1214/19-PS336. [Google Scholar]
  5. Rodríguez-Lallena JA, Úbeda-Flores M (2004), A new class of bivariate copulas. Stat Probab Lett 66, 3, 315–325. https://doi.org/10.1016/j.spl.2003.09.010. [CrossRef] [Google Scholar]
  6. Nelsen RB (2006), An introduction to copulas, Springer-Verlag, New York. https://doi.org/10.1007/0-387-28678-0. [Google Scholar]
  7. Eyraud H (1938), Les principes de la mesure des correlations. Ann Univ Lyon Series A 1, 30–47. [Google Scholar]
  8. Ali MM, Mikhail NN, Haq MS (1978), A class of bivariate distributions including the bivariate logistic. J Multivar Anal 8, 3, 405–412. https://doi.org/10.1016/0047-259X(78)90063-5. [CrossRef] [Google Scholar]
  9. Hougaard P (1986), A class of multivariate failure time distributions. Biometrika 73, 3, 671–678. https://doi.org/10.1093/biomet/73.3.671. [Google Scholar]
  10. Quesada-Molina JJ, Rodríguez-Lallena JA (1995), Bivariate copulas with quadratic sections. J Nonparametr Statist 5, 4, 323–337. https://doi.org/10.1080/10485259508832652. [CrossRef] [Google Scholar]
  11. Nelsen RB, Quesada-Molina JJ, Rodríguez-Lallena JA (1997), Bivariate copulas with cubic sections. J Nonparametr Statist 7, 3, 205–220. https://doi.org/10.1080/10485259708832700. [CrossRef] [Google Scholar]
  12. Lai CD, Xie M (2000), A new family of positive quadrant dependent bivariate distributions. Stat Probab Lett 46, 4, 359–364. https://doi.org/10.1016/S0167-7152(99)00122-4. [CrossRef] [Google Scholar]
  13. Amblard C, Girard S (2002), Symmetry and dependence properties within a semiparametric family of bivariate copulas. J Nonparametr Statist 14, 6, 715–727. https://doi.org/10.1080/10485250215322. [CrossRef] [Google Scholar]
  14. García JE, González-López VA, Nelsen RB (2016), The structure of the class of maximum Tsallis–Havrda–Chavát Entropy Copulas. Entropy 18, 7, 264. https://doi.org/10.3390/e18070264. [CrossRef] [Google Scholar]
  15. Fernández M, González-López VA, Rifo LR (2015), A note on conjugate distributions for copulas. Math Methods Appl Sci 38, 18, 4797–4803. https://doi.org/10.1002/mma.3394. [CrossRef] [Google Scholar]
  16. Clayton DG (1978), A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 65, 1, 141–151. https://doi.org/10.1093/biomet/65.1.141. [CrossRef] [Google Scholar]
  17. Joe H (2014), Dependence modeling with copulas. Chapman and Hall/CRC, New York. https://doi.org/10.1201/b17116. [CrossRef] [Google Scholar]
  18. O’Neill B (2009), Exchangeability, correlation, and bayes’ effect. Int Stat Rev 77, 2, 241–250. https://doi.org/10.1111/j.1751-5823.2008.00059.x. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.