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On the geometric compounding model with applications

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EN
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Under the geometric compounding model, we first investigate the relationship between the compound geometric distribution and the underlying distribution, including the preservation of the infinite divisibility property. An interesting upper bound for the tail probability of the compound geometric distribution is provided by using only the mean of the underlying distribution. Secondly, we apply the obtained results to understand better the L-class of life distributions. In particular, we strengthen a surprising result of Bhattacharjee and Sengupta [5] and show that there are life distributions FєL with the following properties: (i) the support of F consists of countably infinite points, (ii) (ii) the coefficient of variation of F is equal to one, and (iii) (iii) F is not in the HNBUE class (the harmonic new better than used in expectation class).Finally, we apply geometric compounds to characterize the semi-Mittag-Leffler distribution and extend a known result about the exponential distribution.
Rocznik
Strony
135--147
Opis fizyczny
Bibliogr.29 poz.
Twórcy
autor
  • Department of Business Education National Changhua University of Education Changhua 50058 Taiwan, Republic of China
autor
  • Institute of Statistical Science Academia Sinica Taipei 11529 Taiwan, Republic of China
Bibliografia
  • [1] B. C. Arnold, Some characterizations of the exponential distribution by geometric compounding, SIAM J. Appl. Math. 24 (1973), pp. 242-244.
  • [2] T. A. Azlarov, A. A. DzamirzaeV and M. M. Sultanova, Characterizing properties of the exponential distribution, and their stability (in Russian), Random Processes and Statistical Inference, No. II, 94 (1972), pp. 10-19, Izdat. „Fan” Uzbek, SSR, Tashkent. [MR 48 (1974) 3150].
  • [3] T. A. Azlarov and N. A. Volodin, Characterization Problems Associated with the Exponential Distribution (translated by Margaret Stein and edited by Ingram Olkin), Springer, New York 1986.
  • [4] S. K. Basu and M. C. Bhattacharjee, On weak convergence within the HNBUE family of life distributions, J. Appl. Probab. 21 (1984), pp. 65A-660.
  • [5] A. Bhattacharjee and D. Sengupta, On the coefficient of variation of the ℒ - and ℒ -classes, Statist. Probab. Lett. 27 (1996), pp, 177-180.
  • [6] M. Brown, Error bounds for exponential approximations of geometric convolutions, Ann. Probab. 18 (1990), pp. 1388-1402.
  • [7] P. Embrechts, C. Klüppelberg and T. Mikosch, Modelling Extremal Events for Insurance and Finance, Appl. Math. 33, Springer, New York 1997.
  • [8] I. B. Gertsbakh, Asymptotic methods in reliability theory: a review, Adv. in Appl. Probab. 16 (1984), pp. 147-175.
  • [9] B. V. Gnedenko, Limit theorems for sums of a random number of positive independent random variables, in: Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics and Probability, Univ. California Press, Berkeley 1970, pp. 537-549.
  • [10] G. H. Hardy, J. E. Little wood and G. Pólya, Inequalities, 2nd edition, Cambridge University Press, Cambridge 1952.
  • [11] K. Jayakumar and R. N. Pillai, The first-order autoregressive Mittag-Leffler process, J. Appl. Probab. 30 (1993), pp. 462-466.
  • [12] V. Kalashnikov, Geometric Sums: Bounds for Rare Events with Applications, Risk Analysis, Reliability, Queueing, Math. Appl. 413, Kluwer Academic Publishers, London 1997.
  • [13] B. Klefsjö, The HNBUE and HNWUE classes of life distributions, Naval Res. Logist. Quart. 29 (1982), pp. 331-344.
  • [14] B. Klefsjö, A useful ageing property based on the Laplace transform, J. Appl. Probab. 20 (1983), pp. 615-626.
  • [15] I. N. Kovalenko, On the class of limiting distributions for thinning streams of homogeneous events (in Russian), Litovsk. Mat. Sb. 5 (1965), pp. 569-573.
  • [16] I. N. Kovalenko, Rare events in queueing systems. A survey, Queueing Systems Theory Appl. 16 (1994), pp. 1-49.
  • [17] G. D. Lin, Characterizations of the exponential distribution via the blocking time in a queueing system, Statist. Sinica 3 (1993), pp. 577-581.
  • [18] G. D. Lin, Characterizations of the Laplace and related distributions via geometric compound, Sankhya, Series A, 56 (1994), pp. 1-9.
  • [19] G. D. Lin, A note on the Linnik distributions, J. Math. Anal. Appl. 217 (1998), pp. 701-706.
  • [20] G. D. Lin, Characterizations of the IF-class of life distributions, Statist. Probab. Lett. 40 (1998), pp. 259-266.
  • [21] G. D. Lin, On the Mittag-Leffler distributions, J. Statist. Plann. Inference 74 (1998), pp. 1-9.
  • [22] G. D. Lin and C.-Y. Hu, Characterizations of distributions via the stochastic ordering property of random linear forms, Statist. Probab. Lett. 51 (2001), pp. 93-99.
  • [23] E. Lukács, Characteristic Functions, 2nd edition, revised and enlarged, Hafner Publishing Co., New York 1970.
  • [24] R. N. Pillai, Renewal process with Mittag-Leffler waiting time, presented at the 21st Annual Conference of Operational Research Society of India, Opsearch, 26 (1988), p. 57,
  • [25] R. N. Pillai, On Mittag-Leffler functions and related distributions, Ann. Inst. Statist. Math. 42 (1990), pp. 157-161.
  • [26] T. Rolski, H. Schmidli, V. Schmidt and J. Teugels, Stochastic Processes for Insurance and Finance, Wiley Series in Probability and Statistics, Wiley, New York 1999.
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  • [29] R. Szekli, Stochastic Ordering and Dependence in Applied Probability, Lecture Notes in Statist. 97, Springer, New York 1995.
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Bibliografia
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