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Archimedean-based Marshall-Olkin distributions and related dependence structures. (English) Zbl 1392.62047

Summary: In this paper we study the dependence properties of a family of bivariate distributions (that we call Archimedean-based Marshall-Olkin distributions) that extends the class of the generalized Marshall-Olkin distributions of X. Li and F. Pellerey [J. Multivariate Anal. 102, No. 10, 1399–1409 (2011; Zbl 1221.60014)] in order to allow for an Archimedean type of dependence among the underlying shocks’ arrival times. The associated family of copulas (that we call Archimedean-based Marshall-Olkin copulas) includes several well known copula functions as specific cases for which we provide a different costruction and represents a particular case of implementation of P. M. Morillas [Metrika 61, No. 2, 169–184 (2005; Zbl 1079.62056)] construction. It is shown that Archimedean-based copulas are obtained through suitable transformations of bivariate Archimedean copulas: this induces asymmetry, and the corresponding Kendall’s function and Kendall’s tau as well as the tail dependence parameters are studied. The type of dependence so modeled is wide and illustrated through examples and the validity of the weak Lack of memory property (characterizing the Marshall-Olkin distribution) is also investigated and the sub-family of distributions satisfying it identified. Moreover, the main theoretical results are extended to the multidimensional version of the considered distributions and estimation issues discussed.

MSC:

62E15 Exact distribution theory in statistics
60E05 Probability distributions: general theory
62H20 Measures of association (correlation, canonical correlation, etc.)

References:

[1] Aczél J (1966) Lectures on Functional Equations and Their Applications. Academic Press, New York · Zbl 0139.09301
[2] Alsina C, Frank MJ, Schweizer B (2006) Associative functions: triangular norms and copulas. World Scientific, Singapore · Zbl 1100.39023 · doi:10.1142/6036
[3] Asimit V, Furman E, Vernic R (2010) On a Multivariate Pareto Distribution. Insurance: Mathematics and Economics 46(2):308-316 · Zbl 1231.60013
[4] Asimit V, Furman E, Vernic R (2016) Statistical Inference for a New Class of Multivariate Pareto Distributions. Commun Stat Simul Comput 45(2):456-471 · Zbl 1341.62113 · doi:10.1080/03610918.2013.861627
[5] Baglioni A, Cherubini U (2013) Within and between systemic country risk: theory and evidence from the sovereign crisis in Europe. J Econ Dyn Control 37:1581-1597 · Zbl 1327.91066 · doi:10.1016/j.jedc.2013.02.005
[6] Bernhart G, Escobar Anel M, Mai JF, Scherer M (2013) Default models based on scale mixtures of Marshall-Olkin Copulas: properties and applications. Metrika 76(2):179-203 · Zbl 1430.91121 · doi:10.1007/s00184-012-0382-z
[7] Capéraà P, Fougères A-L, Genest C (2000) Bivariate distributions with given extreme value attractor. J Multivar Anal 72(1):30-49 · Zbl 0978.62043 · doi:10.1006/jmva.1999.1845
[8] Charpentier A (2003) Tail distribution and dependence measure. Proceedings of the 34th ASTIN Conference · Zbl 1392.62157
[9] Charpentier A (2006) Dependence structure and limiting results with applications in finance and insurance. PhD thesis, Katholieke Universiteit of Leuven · Zbl 0694.62050
[10] Cherubini U, Mulinacci S (2015) Systemic Risk with Exchangeable Contagion: Application to the European Banking Systems. arXiv:1502.01918 · Zbl 1221.60014
[11] Dempster AP, Laird M, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algoriyhm. J R Stat Soc Ser B 39(1):1-38 · Zbl 0364.62022
[12] Durante F, Quesada-Molina JJ, Sempi C (2007) A generalization of the Archimedean class of bivariate copulas. AISM 59:487-498 · Zbl 1332.62171 · doi:10.1007/s10463-006-0061-9
[13] Durante F, Salvadori G (2010) On the construction of multivariate extreme value models via copulas. Environmetrics 21(2):143-161
[14] Genest C, Rivest L-P (1993) Statistical Inference Procedures for Bivariate Archimedean Copulas. J Am Stat Assoc 88(423):1034-1043 · Zbl 0785.62032 · doi:10.1080/01621459.1993.10476372
[15] Karlis D (2003) ML estimation for multivariate shock models via an EM algorithm. Ann Inst Stat Math 55(4):817-830 · Zbl 1047.62052 · doi:10.1007/BF02523395
[16] Kundu D, Dey AK (2009) Estimating the parameters of the Marshall-Olkin bivariate Weibull distribution by EM algorithm. Comput Stat Data Anal 53(4):956-965 · Zbl 1452.62728 · doi:10.1016/j.csda.2008.11.009
[17] Kundu D, Gupta AK (2013) Bayes estimation for the Marshall-Olkin bivariate Weibull distribution. Comput Stat Data Anal 57(1):271-281 · Zbl 1365.62096 · doi:10.1016/j.csda.2012.06.002
[18] Li H (2009) Orthant tail dependence of multivariate extreme value distributions. J Multivar Anal 100(1):243-256 · Zbl 1151.62041 · doi:10.1016/j.jmva.2008.04.007
[19] Li X, Pellerey F (2011) Generalized Marshall-Olkin Distributions and Related Bivariate Aging Properties. J Multivar Anal 102(10):1399-1409 · Zbl 1221.60014 · doi:10.1016/j.jmva.2011.05.006
[20] Lin J, Li X (2014) Multivariate Generalized Marshall-Olkin Distributions and Copulas. Methodol Comput Appl Probab 16(1):53-78 · Zbl 1291.60031 · doi:10.1007/s11009-012-9297-4
[21] Lu JC (1989) Weibull extension of the Freund and Marshall-Olkin bivariate exponential models. IEEE Trans Reliab 38:615-619 · Zbl 0694.62050 · doi:10.1109/24.46492
[22] Mai JF, Scherer M, Zagst R (2013) CIID frailty models and implied copulas. In: Copulae in Mathematical and Quantitative Finance, Lecture Notes in Statistics 213. Springer Verlag, pp 201-230 · Zbl 1273.62070
[23] Marichal J-L, Mathonet P (2011) Extensions of system signatures to dependent lifetimes: Explicit expressions and interpretations. J Multivar Anal 102(5):931-936 · Zbl 1215.62108
[24] Marshall AW, Olkin I (1967) A multivariate exponential distribution. J Amer Statist Ass 62(317):30-44 · Zbl 0147.38106 · doi:10.1080/01621459.1967.10482885
[25] Marshall AW, Olkin I (1988) Families of Multivariate Distributions. J Amer Statist Ass 83(403):834-841 · Zbl 0683.62029 · doi:10.1080/01621459.1988.10478671
[26] Mazo G, Girard S, Forbes F (2015) Weighted least-squares inference for multivariate copulas based on dependence coefficients. ESAIM: Probability and Statistics 19:746-765 · Zbl 1392.62157 · doi:10.1051/ps/2015014
[27] McNeil AJ, Nešlehová J (2009) Multivariate Archimedean copulas, d-monotone functions and l1-norm symmetric distributions. Ann Stat 37:3059-3097 · Zbl 1173.62044 · doi:10.1214/07-AOS556
[28] McNeil AJ, Nešlehová J (2010) From Archimedean to Liouville copulas. J Multivar Anal 101(8):1772-1790 · Zbl 1190.62102 · doi:10.1016/j.jmva.2010.03.015
[29] Morillas PM (2005) A method to obtain new copulas from a given one. Metrika 61(2):169-184 · Zbl 1079.62056 · doi:10.1007/s001840400330
[30] Mulero J, Pellerey F (2010) Bivariate Aging Properties under Archimedean Dependence Structures. Communications in Statistics - Theory and Methods 39:3108-3121 · Zbl 1201.62112 · doi:10.1080/03610920903199987
[31] Muliere P, Scarsini M (1987) Characterization of a Marshall-Olkin type Class of Distributions. Ann Ist Stat Math 39(1):429-441 · Zbl 0624.62047
[32] Mulinacci, S.; Cherubini, U. (ed.); Durante, F. (ed.); Mulinacci, S. (ed.), Marshall-Olkin Machinery and Power Mixing: The Mixed Generalized Marshall-Olkin Distribution, 65-86 (2015), Switzerland · Zbl 1365.62190 · doi:10.1007/978-3-319-19039-6_5
[33] Nelsen RB (2006) An Introduction to Copulas. Springer, 2nd Edn. · Zbl 1152.62030
[34] Oakes D (2005) On the preservation of copula structure under truncation. Can J Stat 33(3):465-468 · Zbl 1101.62040 · doi:10.1002/cjs.5540330310
[35] Pinto J, Kolev N (2015) Extended Marshall-Olkin Model and Its Dual Version. In: Cherubini U, Durante F, Mulinacci S (eds) Marshall-Olkin Distributions-Advances in Theory and Applications. Springer Proceedings in Mathematics and Statistics 141. Springer International Publishing Switzerland, pp 87-113 · Zbl 1365.62191
[36] Samaniego FJ (2007) System signatures and their applications in engineering reliability. Volume 110, Springer · Zbl 1154.62075
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