IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v119y2016icp357-362.html
   My bibliography  Save this article

The limit theorem for maximum of partial sums of exchangeable random variables

Author

Listed:
  • Alonso Ruiz, Patricia
  • Rakitko, Alexander

Abstract

We obtain the analogue of the classical result by Erdös and Kac on the limiting distribution of the maximum of partial sums for exchangeable random variables with zero mean and variance one. We show that, if the conditions of the central limit theorem of Blum et al. hold, the limit coincides with the classical one. Under more general assumptions, the probability of the random variables having conditional negative drift appears in the limit.

Suggested Citation

  • Alonso Ruiz, Patricia & Rakitko, Alexander, 2016. "The limit theorem for maximum of partial sums of exchangeable random variables," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 357-362.
    • Handle: RePEc:eee:stapro:v:119:y:2016:i:c:p:357-362
    DOI: 10.1016/j.spl.2016.09.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715216301730
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2016.09.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gerardi, Anna & Spizzichino, Fabio & Torti, Barbara, 2000. "Exchangeable mixture models for lifetimes: the role of "occupation numbers"," Statistics & Probability Letters, Elsevier, vol. 49(4), pages 365-375, October.
    2. Yu, Chang & Zelterman, Daniel, 2008. "Sums of exchangeable Bernoulli random variables for family and litter frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1636-1649, January.
    3. Berti, Patrizia & Rigo, Pietro, 1997. "A Glivenko-Cantelli theorem for exchangeable random variables," Statistics & Probability Letters, Elsevier, vol. 32(4), pages 385-391, April.
    4. B. Prakasa Rao, 2009. "Conditional independence, conditional mixing and conditional association," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(2), pages 441-460, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qi Guo & Bruno Remillard & Anatoliy Swishchuk, 2020. "Multivariate General Compound Point Processes in Limit Order Books," Risks, MDPI, vol. 8(3), pages 1-20, September.
    2. Kolossiatis, M. & Griffin, J.E. & Steel, M.F.J., 2011. "Modeling overdispersion with the normalized tempered stable distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2288-2301, July.
    3. Hadjikyriakou, Milto, 2013. "Comparison of conditional expectations of functions of strong N-demimartingales and functions of sums of conditionally independent random variables," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1282-1286.
    4. Bryan S. Graham, 2017. "An econometric model of network formation with degree heterogeneity," CeMMAP working papers 08/17, Institute for Fiscal Studies.
    5. Liangjun Su & Zhentao Shi & Peter C. B. Phillips, 2016. "Identifying Latent Structures in Panel Data," Econometrica, Econometric Society, vol. 84, pages 2215-2264, November.
    6. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    7. Spizzichino, F. & Torrisi, G. L., 2001. "Multivariate negative aging in an exchangeable model of heterogeneity," Statistics & Probability Letters, Elsevier, vol. 55(1), pages 71-82, November.
    8. repec:spo:wpecon:info:hdl:2441/2etjsneok98utpcm5s44jn4dlh is not listed on IDEAS
    9. Bowman, Dale, 2016. "Statistical inference for familial disease models assuming exchangeability," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 220-225.
    10. Koen Jochmans, 2018. "Semiparametric Analysis of Network Formation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 705-713, October.
    11. Castagnetti, Carolina & Rossi, Eduardo & Trapani, Lorenzo, 2019. "A two-stage estimator for heterogeneous panel models with common factors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 63-82.
    12. Djehiche, Boualem & Löfdahl, Björn, 2014. "Risk aggregation and stochastic claims reserving in disability insurance," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 100-108.
    13. G. Forchini & Bin Jiang & Bin Peng, 2015. "Common Shocks in panels with Endogenous Regressors," Monash Econometrics and Business Statistics Working Papers 8/15, Monash University, Department of Econometrics and Business Statistics.
    14. Giovanni Forchini & Bin Jiang & Bin Peng, 2018. "TSLS and LIML Estimators in Panels with Unobserved Shocks," Econometrics, MDPI, vol. 6(2), pages 1-12, April.
    15. Giovanni Forchini & Bin Peng, 2016. "A Conditional Approach to Panel Data Models with Common Shocks," Econometrics, MDPI, vol. 4(1), pages 1-12, January.
    16. Luis E. Candelaria, 2020. "A Semiparametric Network Formation Model with Unobserved Linear Heterogeneity," Papers 2007.05403, arXiv.org, revised Aug 2020.
    17. Su, Liangjun & Jin, Sainan & Zhang, Yonghui, 2015. "Specification test for panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 186(1), pages 222-244.
    18. Wang, Xinghui & Wang, Xuejun, 2013. "Some inequalities for conditional demimartingales and conditional N-demimartingales," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 700-709.
    19. Ash Abebe & Huybrechts F. Bindele & Masego Otlaadisa & Boikanyo Makubate, 2021. "Robust estimation of single index models with responses missing at random," Statistical Papers, Springer, vol. 62(5), pages 2195-2225, October.
    20. Balakrishnan, Narayanaswamy & Barmalzan, Ghobad & Haidari, Abedin, 2016. "Multivariate stochastic comparisons of multivariate mixture models and their applications," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 37-43.
    21. Manel Kacem & Stéphane Loisel & Véronique Maume-Deschamps, 2016. "Some mixing properties of conditionally independent processes," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(5), pages 1241-1259, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:119:y:2016:i:c:p:357-362. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.