On tests for distinguishing distribution tails
Teoriâ veroâtnostej i ee primeneniâ, Tome 66 (2021) no. 3, pp. 433-453 Cet article a éte moissonné depuis la source Math-Net.Ru

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We propose a test procedure for distinguishing between two separable classes of arbitrary distribution tails and, moreover, prove its consistency. The method is based on the goodness-of-fit test for an arbitrary distribution tail, and properties of this test are also discussed. This is the first goodness-of-fit test for distribution tails proposed in the literature that can be applied for testing the goodness-of-fit hypothesis with a discrete distribution tail. In contrast to the overwhelming majority of works related to statistics of extremes, we do not assume that the distributions belong to any of maximum domains of attraction.
Keywords: discrimination test, statistics of extremes, goodness-of-fit test
Mots-clés : distribution tail.
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N. S. Kogut; I. V. Rodionov. On tests for distinguishing distribution tails. Teoriâ veroâtnostej i ee primeneniâ, Tome 66 (2021) no. 3, pp. 433-453. http://geodesic.mathdoc.fr/item/TVP_2021_66_3_a1/

[1] Woochul Lim, Tae Hee Lee, Seunghoon Kang, Su-gil Cho, “Estimation of body and tail distribution under extreme events for reliability analysis”, Struct. Multidiscip. Optim., 54:6 (2016), 1631–1639 | DOI | MR

[2] J. Luckstead, S. Devadoss, “Pareto tails and lognormal body of US cities size distribution”, Phys. A, 465 (2017), 573–578 | DOI

[3] L. de Haan, A. Ferreira, Extreme value theory. An introduction, Springer Ser. Oper. Res. Financ. Eng., Springer, New York, 2006, xviii+417 pp. | DOI | MR | Zbl

[4] J. Beirlant, Yu. Goegebeur, J. Teugels, J. Segers, Statistics of extremes. Theory and applications, Wiley Ser. Probab. Stat., John Wiley Sons, Ltd., Chichester, 2004, xiv+490 pp. | DOI | MR | Zbl

[5] P. Embrechts, C. Klüppelberg, T. Mikosch, Modelling extremal events for insurance and finance, Appl. Math. (N. Y.), 33, Springer-Verlag, Berlin, 1997, xvi+645 pp. | DOI | MR | Zbl

[6] B. Gnedenko, “Sur la distribution limite du terme maximum d'une série aléatoire”, Ann. of Math. (2), 44:3 (1943), 423–453 | DOI | MR | Zbl

[7] M. I. Gomes, “Generalized Gumbel and likelihood ratio test statistics in the multivariate GEV model”, Comput. Stat. Data Anal., 7:3 (1989), 259–267 | DOI | MR | Zbl

[8] J. Z. Wang, P. Cooke, S. Li, “Determination of domains of attraction based on a sequence of maxima”, Austral. J. Statist., 38:2 (1996), 173–181 | DOI | MR | Zbl

[9] D. Dietrich, L. de Haan, J. Hüsler, “Testing extreme value conditions”, Extremes, 5:1 (2002), 71–85 | DOI | MR | Zbl

[10] J. Beirlant, T. de Wet, Y. Goegebeur, “A goodness-of-fit statistic for Pareto-type behaviour”, J. Comput. Appl. Math., 186:1 (2006), 99–116 | DOI | MR | Zbl

[11] A. J. Koning, Liang Peng, “Goodness-of-fit tests for a heavy tailed distribution”, J. Statist. Plann. Inference, 138:12 (2008), 3960–3981 | DOI | MR | Zbl

[12] J. Hüsler, Liang Peng, “Review of testing issues in extremes: in honor of Professor Laurens de Haan”, Extremes, 11:1 (2008), 99–111 | DOI | MR | Zbl

[13] M. I. Gomes, A. Guillou, “Extreme value theory and statistics of univariate extremes: a review”, Int. Stat. Rev., 83:2 (2015), 263–292 | DOI | MR

[14] I. Malevergne, V. Pisarenko, D. Sornette, “Empirical distributions of stock returns: between the stretched exponential and the power law?”, Quant. Finance, 5:4 (2005), 379–401 | DOI | MR | Zbl

[15] M. Fitzka, J. Hadzimustafic, S. Simic, “Total ozone and Umkehr observations at Hoher Sonnblick 1994–2011: Climatology and extreme events”, J. Geophys. Res., 119:2 (2014), 739–752 | DOI

[16] I. Fraga Alves, L. de Haan, C. Neves, “A test procedure for detecting super-heavy tails”, J. Statist. Plann. Inference, 139:2 (2009), 213–227 | DOI | MR | Zbl

[17] J. Goegebeur, A. Guillou, “Goodness-of-fit testing for Weibull-type behavior”, J. Statist. Plann. Inference, 140:6 (2010), 1417–1436 | DOI | MR | Zbl

[18] I. V. Rodionov, “A discrimination test for tails of Weibull-type distributions”, Theory Probab. Appl., 63:2 (2018), 327–335 | DOI | DOI | MR | Zbl

[19] I. V. Rodionov, “Discrimination of close hypotheses about the distribution tails using higher order statistics”, Theory Probab. Appl., 63:3 (2019), 364–380 | DOI | DOI | MR | Zbl

[20] I. V. Rodionov, “On discrimination between classes of distribution tails”, Probl. Inf. Transm., 54:2 (2018), 124–138 | DOI | MR | Zbl

[21] N. M. Markovich, I. V. Rodionov, “Threshold selection for extremal index estimation”, Scand. J. Stat., 2020 (to appear); arXiv: 2009.02318

[22] E. O. Kantonistova, I. V. Rodionov, “Analogues of classical goodness-of-fit tests for distribution tails”, Dokl. Math., 103:1 (2021), 35–38 | DOI | DOI

[23] I. V. Rodionov, “Inferences on parametric estimation of distribution tails”, Dokl. Math., 100:2 (2019), 456–458 | DOI | DOI | Zbl

[24] I. V. Rodionov, “On estimation of Weibull-tail and log-Weibull-tail distributions for modeling end-to-end delay”, DCCN 2019: Distributed computer and communication networks, Commun. Comput. Inf. Sci., 1141, Springer, Cham, 2019, 302–314 | DOI

[25] M. R. Leadbetter, G. Lindgren, H. Rootzén, Extremes and related properties of random sequences and processes, Springer Ser. Statist., Springer-Verlag, New York–Berlin, 1983, xii+336 pp. | DOI | MR | MR | Zbl | Zbl

[26] Yu. A. Pesenko, Printsipy i metody kolichestvennogo analiza v faunisticheskikh issledovaniyakh, Nauka, M., 1982, 287 pp.

[27] M. Falk, “Some best parameter estimates for distributions with finite endpoint”, Statistics, 27:1-2 (1995), 115–125 | DOI | MR | Zbl

[28] P. I. Akhtyamov, I. V. Rodionov, “Ob otsenke parametrov sdviga i masshtaba khvostov raspredelenii”, Fundament. i prikl. matem., 23:1 (2020), 25–49 | MR

[29] J. Beirlant, M. Broniatowski, J. L. Teugels, P. Vynckier, “The mean residual life function at great age: applications to tail estimation”, J. Statist. Plann. Inference, 45:1-2 (1995), 21–48 | DOI | MR | Zbl

[30] O. A. Y. Jackson, “An analysis of departures from the exponential distribution”, J. Roy. Statist. Soc. Ser. B, 29 (1967), 540–549 | DOI | MR | Zbl

[31] P. A. W. Lewis, “Some results on tests for Poisson processes”, Biometrika, 52:1-2 (1965), 67–77 | DOI | MR | Zbl

[32] O. Kardaun, “Statistical survival analysis of male larynx-cancer patients – a case study”, Statist. Neerlandica, 37:3 (1983), 103–125 | DOI

[33] J. P. Klein, M. L. Moeschberger, Survival analysis: techniques for censored and truncated data, 2nd ed., Springer, New York, 2003, xv+536 pp. | DOI | Zbl

[34] M. I. Gomes, M. M. Neves, “Estimation of the extreme value index for randomly censored data”, Biometrical Lett., 48:1 (2011), 1–22

[35] J. Worms, R. Worms, “Estimation of extremes for Weibull-tail distributions in the presence of random censoring”, Extremes, 22:4 (2019), 667–704 | DOI | MR | Zbl