IDEAS home Printed from https://ideas.repec.org/a/csb/stintr/v17y2016i3p541-556.html
   My bibliography  Save this article

Kernel Estimation of Cumulative Distribution Function of a Random Variable with Bounded Support

Author

Listed:
  • Aleksandra Baszczyńska

Abstract

In the paper methods of reducing the so-called boundary effects, which appear in the estimation of certain functional characteristics of a random variable with bounded support, are discussed. The methods of the cumulative distribution function estimation, in particular the kernel method, as well as the phenomenon of increased bias estimation in boundary region are presented. Using simulation methods, the properties of the modified kernel estimator of the distribution function are investigated and an attempt to compare the classical and the modified estimators is made.

Suggested Citation

  • Aleksandra Baszczyńska, 2016. "Kernel Estimation of Cumulative Distribution Function of a Random Variable with Bounded Support," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(3), pages 541-556, September.
  • Handle: RePEc:csb:stintr:v:17:y:2016:i:3:p:541-556
    as

    Download full text from publisher

    File URL: http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v17_2016_i3_n11.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Karunamuni, R.J. & Zhang, S., 2008. "Some improvements on a boundary corrected kernel density estimator," Statistics & Probability Letters, Elsevier, vol. 78(5), pages 499-507, April.
    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. Berry, Tyrus & Sauer, Timothy, 2017. "Density estimation on manifolds with boundary," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 1-17.
    2. Tongyun Du & Henrik Vejre & Christian Fertner & Pengcheng Xiang, 2019. "Optimisation of Ecological Leisure Industrial Planning Based on Improved GIS-AHP: A Case Study in Shapingba District, Chongqing, China," Sustainability, MDPI, vol. 12(1), pages 1-29, December.
    3. Chaubey, Yogendra P. & Dewan, Isha & Li, Jun, 2011. "Smooth estimation of survival and density functions for a stationary associated process using Poisson weights," Statistics & Probability Letters, Elsevier, vol. 81(2), pages 267-276, February.
    4. Baszczyńska Aleksandra, 2016. "Kernel Estimation of Cumulative Distribution Function of a Random Variable with Bounded Support," Statistics in Transition New Series, Statistics Poland, vol. 17(3), pages 541-556, September.
    5. Gabrielli, M. Florencia & Willington, Manuel, 2023. "Estimating damages from bidding rings in first-price auctions," Economic Modelling, Elsevier, vol. 126(C).
    6. Cattaneo, Matias D. & Jansson, Michael & Ma, Xinwei, 2024. "Local regression distribution estimators," Journal of Econometrics, Elsevier, vol. 240(2).
    7. Shunpu Zhang & Rohana Karunamuni, 2010. "Boundary performance of the beta kernel estimators," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(1), pages 81-104.
    8. Gensler, André & Sick, Bernhard & Vogt, Stephan, 2018. "A review of uncertainty representations and metaverification of uncertainty assessment techniques for renewable energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 352-379.
    9. Ma, Jun & Marmer, Vadim & Shneyerov, Artyom, 2019. "Inference for first-price auctions with Guerre, Perrigne, and Vuong’s estimator," Journal of Econometrics, Elsevier, vol. 211(2), pages 507-538.
    10. Joris Pinkse & Karl Schurter, 2020. "Estimates of derivatives of (log) densities and related objects," Papers 2006.01328, arXiv.org.
    11. Joris Pinkse & Karl Schurter, 2019. "Estimation of Auction Models with Shape Restrictions," Papers 1912.07466, arXiv.org.
    12. Taflanidis, Alexandros A. & Loukogeorgaki, Eva & Angelides, Demos C., 2013. "Offshore wind turbine risk quantification/evaluation under extreme environmental conditions," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 19-32.
    13. Aleksandra Baszczyńska, 2016. "Kernel Estimation Of Cumulative Distribution Function Of A Random Variable With Bounded Support," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 541-556, September.

    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:csb:stintr:v:17:y:2016:i:3:p:541-556. 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: Beata Witek (email available below). General contact details of provider: https://edirc.repec.org/data/gusgvpl.html .

    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.