IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v118y2016icp37-44.html
   My bibliography  Save this article

Deconvolution of a discrete uniform distribution

Author

Listed:
  • Zhigljavsky, Anatoly
  • Golyandina, Nina
  • Gryaznov, Svyatoslav

Abstract

Let ξ be a discrete random variable (r.v.) with uniform distribution on the support set {0,1,…,N}. We study the problem of construction of non-degenerate independent r.v.’s ξ1 and ξ2 such that ξ=ξ1+ξ2, if these r.v.’s exist. We describe a general form for the solutions to this problem, offer some analytic constructions and develop algorithms for computing the distributions of ξ1 and ξ2.

Suggested Citation

  • Zhigljavsky, Anatoly & Golyandina, Nina & Gryaznov, Svyatoslav, 2016. "Deconvolution of a discrete uniform distribution," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 37-44.
    • Handle: RePEc:eee:stapro:v:118:y:2016:i:c:p:37-44
    DOI: 10.1016/j.spl.2016.06.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715216300876
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2016.06.006?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. Jonathan Gillard & Anatoly Zhigljavsky, 2013. "Optimization challenges in the structured low rank approximation problem," Journal of Global Optimization, Springer, vol. 57(3), pages 733-751, November.
    2. Genevera I. Allen & Logan Grosenick & Jonathan Taylor, 2014. "A Generalized Least-Square Matrix Decomposition," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 145-159, March.
    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. Hongtu Zhu & Dan Shen & Xuewei Peng & Leo Yufeng Liu, 2017. "MWPCR: Multiscale Weighted Principal Component Regression for High-Dimensional Prediction," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1009-1021, July.
    2. Gillard, Jonathan & Usevich, Konstantin, 2018. "Structured low-rank matrix completion for forecasting in time series analysis," International Journal of Forecasting, Elsevier, vol. 34(4), pages 582-597.
    3. Yaroslav D. Sergeyev & Marat S. Mukhametzhanov & Dmitri E. Kvasov & Daniela Lera, 2016. "Derivative-Free Local Tuning and Local Improvement Techniques Embedded in the Univariate Global Optimization," Journal of Optimization Theory and Applications, Springer, vol. 171(1), pages 186-208, October.
    4. Sergeyev, Yaroslav D. & Kvasov, Dmitri E. & Mukhametzhanov, Marat S., 2017. "Operational zones for comparing metaheuristic and deterministic one-dimensional global optimization algorithms," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 141(C), pages 96-109.
    5. Fithian, William & Josse, Julie, 2017. "Multiple correspondence analysis and the multilogit bilinear model," Journal of Multivariate Analysis, Elsevier, vol. 157(C), pages 87-102.

    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:118:y:2016:i:c:p:37-44. 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.