Modern Stochastics: Theory and Applications logo


  • Help
Login Register

  1. Home
  2. Issues
  3. Volume 9, Issue 2 (2022)
  4. Asymptotic results for families of rando ...

Modern Stochastics: Theory and Applications

Submit your article Information Become a Peer-reviewer
  • Article info
  • Full article
  • Related articles
  • Cited by
  • More
    Article info Full article Related articles Cited by

Asymptotic results for families of random variables having power series distributions
Volume 9, Issue 2 (2022), pp. 207–228
Claudio Macci ORCID icon link to view author Claudio Macci details   Barbara Pacchiarotti ORCID icon link to view author Barbara Pacchiarotti details   Elena Villa ORCID icon link to view author Elena Villa details  

Authors

 
Placeholder
https://doi.org/10.15559/21-VMSTA198
Pub. online: 3 February 2022      Type: Research Article      Open accessOpen Access

Received
13 September 2021
Revised
6 December 2021
Accepted
25 December 2021
Published
3 February 2022

Abstract

Suitable families of random variables having power series distributions are considered, and their asymptotic behavior in terms of large (and moderate) deviations is studied. Two examples of fractional counting processes are presented, where the normalizations of the involved power series distributions can be expressed in terms of the Prabhakar function. The first example allows to consider the counting process in [Integral Transforms Spec. Funct. 27 (2016), 783–793], the second one is inspired by a model studied in [J. Appl. Probab. 52 (2015), 18–36].

References

[1] 
Beghin, L., Macci, C.: Large deviations for fractional Poisson processes. Stat. Probab. Lett. 83, 1193–1202 (2013). MR3041393. https://doi.org/10.1016/j.spl.2013.01.017
[2] 
Beghin, L., Macci, C.: Asymptotic results for a multivariate version of the alternative fractional Poisson process. Stat. Probab. Lett. 129, 260–268 (2017). MR3688542. https://doi.org/10.1016/j.spl.2017.06.009
[3] 
Cahoy, D., Di Nardo, E., Polito, F.: Flexible models for overdispersed and underdispersed count data. Stat. Pap. 62, 2969–2990 (2021). MR4332214. https://doi.org/10.1007/s00362-021-01222-7
[4] 
Consul, P.C., Shenton, L.R.: Some interesting properties of Lagrangian distributions. Commun. Stat. 2, 263–272 (1973). MR0408069. https://doi.org/10.1080/03610917308548270
[5] 
del Castillo, J., Pérez-Casany, M.: Weighted Poisson distributions for overdispersion and underdispersion situations. Ann. Inst. Stat. Math. 50, 567–585 (1998). MR1664520. https://doi.org/10.1023/A:1003585714207
[6] 
del Castillo, J., Pérez-Casany, M.: Overdispersed and underdispersed Poisson generalizations. J. Stat. Plan. Inference 134, 486–500 (2005). MR2200069. https://doi.org/10.1016/j.jspi.2004.04.019
[7] 
Dembo, A., Zeitouni, O.: Large Deviations Techniques and Applications, 2nd edn. Springer, New York (1998). MR1619036. https://doi.org/10.1007/978-1-4612-5320-4
[8] 
Embrechts, P., Klüppelberg, C., Mikosch, T.: Modelling Extremal Events. Springer, Berlin (1997). MR1458613. https://doi.org/10.1007/978-3-642-33483-2
[9] 
Gajda, J., Beghin, L.: Prabhakar Lévy processes. Stat. Probab. Lett. 178, 109162 (2021). 9 pp. MR4279303. https://doi.org/10.1016/j.spl.2021.109162
[10] 
Garra, R., Orsingher, E., Polito, F.: State dependent fractional point processes. J. Appl. Probab. 52, 18–36 (2015). MR3336844. https://doi.org/10.1239/jap/1429282604
[11] 
Giusti, A., Colombaro, I., Garra, R., Garrappa, R., Polito, F., Popolizio, M., Mainardi, F.: A practical guide to Prabhakar fractional calculus. Fract. Calc. Appl. Anal. 23, 9–54 (2020). MR4069921. https://doi.org/10.1515/fca-2020-0002
[12] 
Gorenflo, R., Kilbas, A.A., Mainardi, F., Rogosin, S.V.: Mittag-Leffler Functions, Related Topics and Applications. Springer, Heidelberg (2014). MR3244285. https://doi.org/10.1007/978-3-662-43930-2
[13] 
Gupta, P.L., Gupta, R.C., Ong, S.H., Srivastava, H.M.: A class of Hurwitz-Lerch zeta distributions and their applications in reliability. Appl. Math. Comput. 196, 521–531 (2008). MR2388708. https://doi.org/10.1016/j.amc.2007.06.012
[14] 
Gupta, R.C.: Modified power series distribution and some of its applications. Sankhya, Ser. B 36, 288–298 (1974). MR0391334
[15] 
Kemp, A.W.: Families of power series distributions, with particular reference to the Lerch family. J. Stat. Plan. Inference 140, 2255–2259 (2010). MR2609484. https://doi.org/10.1016/j.jspi.2010.01.021
[16] 
Kilbas, A.A., Srivastava, H.M., Trujillo, J.J.: Theory and Applications of Fractional Differential Equations. Elsevier, Boston (2006). MR2218073
[17] 
Luo, M.J., Parmar, R.K., Raina, R.K.: On extended Hurwitz-Lerch zeta function. J. Math. Anal. Appl. 448, 1281–1304 (2017). MR3582282. https://doi.org/10.1016/j.jmaa.2016.11.046
[18] 
Paris, R.B.: Asymptotics of the special functions of fractional calculus. In: Handbook of Fractional Calculus with Applications, vol. 1, pp. 297–325. De Gruyter, Berlin (2019). MR3888406
[19] 
Patil, G.P.: Certain properties of the generalized power series distribution. Ann. Inst. Stat. Math. 14, 179–182 (1962). MR0156395. https://doi.org/10.1007/BF02868639
[20] 
Pogány, T.K., Tomovski, Ž.: Probability distribution built by Prabhakar function. Related Turán and Laguerre inequalities. Integral Transforms Spec. Funct. 27, 783–793 (2016). MR3544402. https://doi.org/10.1080/10652469.2016.1201817

Full article Related articles Cited by PDF XML
Full article Related articles Cited by PDF XML

Copyright
© 2022 The Author(s). Published by VTeX
by logo by logo
Open access article under the CC BY license.

Keywords
Fractional counting processes large deviations moderate deviations Mittag-Leffler functions

MSC2010
60F10 60E05 60G22

Funding
All the authors acknowledge the support of Indam-GNAMPA (research project “Stime asintotiche: principi di invarianza e grandi deviazioni”). Claudio Macci and Barbara Pacchiarotti also acknowledge the support of the MIUR Excellence Department Project awarded to the Department of Mathematics, University of Rome Tor Vergata (CUP E83C18000100006) and of University of Rome Tor Vergata (research program “Beyond Borders”, project “Asymptotic Methods in Probability” (CUP E89C20000680005)).

Metrics
since March 2018
483

Article info
views

332

Full article
views

303

PDF
downloads

113

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

MSTA

MSTA

  • Online ISSN: 2351-6054
  • Print ISSN: 2351-6046
  • Copyright © 2018 VTeX

About

  • About journal
  • Indexed in
  • Editors-in-Chief

For contributors

  • Submit
  • OA Policy
  • Become a Peer-reviewer

Contact us

  • ejournals-vmsta@vtex.lt
  • Mokslininkų 2A
  • LT-08412 Vilnius
  • Lithuania
Powered by PubliMill  •  Privacy policy