IDEAS home Printed from https://ideas.repec.org/a/spr/sistpr/v4y2001i2p181-198.html
   My bibliography  Save this article

Estimating the Distribution Function of a Stationary Process Involving Measurement Errors

Author

Listed:
  • D.A. Ioannides
  • D.P. Papanastassiou

Abstract

No abstract is available for this item.

Suggested Citation

  • D.A. Ioannides & D.P. Papanastassiou, 2001. "Estimating the Distribution Function of a Stationary Process Involving Measurement Errors," Statistical Inference for Stochastic Processes, Springer, vol. 4(2), pages 181-198, May.
  • Handle: RePEc:spr:sistpr:v:4:y:2001:i:2:p:181-198
    DOI: 10.1023/A:1017996326631
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1017996326631
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/A:1017996326631?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. Masry, E., 1993. "Asymptotic Normality for Deconvolution Estimators of Multivariate Densities of Stationary Processes," Journal of Multivariate Analysis, Elsevier, vol. 44(1), pages 47-68, January.
    2. Li, Tong & Vuong, Quang, 1998. "Nonparametric Estimation of the Measurement Error Model Using Multiple Indicators," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 139-165, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Peter Hall & Tapabrata Maiti, 2009. "Deconvolution methods for non‐parametric inference in two‐level mixed models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 703-718, June.

    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. Hao Dong & Taisuke Otsu & Luke Taylor, 2023. "Bandwidth selection for nonparametric regression with errors-in-variables," Econometric Reviews, Taylor & Francis Journals, vol. 42(4), pages 393-419, April.
    2. Yao Luo & Peijun Sang & Ruli Xiao, 2024. "Order Statistics Approaches to Unobserved Heterogeneity in Auctions," Working Papers tecipa-776, University of Toronto, Department of Economics.
    3. Lamy, Laurent, 2012. "The econometrics of auctions with asymmetric anonymous bidders," Journal of Econometrics, Elsevier, vol. 167(1), pages 113-132.
    4. Marianna Pensky & Ahmed Zayed, 2002. "Density Deconvolution of Different Conditional Distributions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(3), pages 701-712, September.
    5. Peter Hall & Tapabrata Maiti, 2009. "Deconvolution methods for non‐parametric inference in two‐level mixed models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 703-718, June.
    6. Kirill S. Evdokimov & Andrei Zeleneev, 2023. "Simple Estimation of Semiparametric Models with Measurement Errors," Papers 2306.14311, arXiv.org, revised Jan 2025.
    7. Manuel Arellano & Stéphane Bonhomme, 2012. "Identifying Distributional Characteristics in Random Coefficients Panel Data Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 987-1020.
    8. Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
    9. Roy, Arkaprava & Sarkar, Abhra, 2023. "Bayesian semiparametric multivariate density deconvolution via stochastic rotation of replicates," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    10. Susan Athey & Philip A. Haile, 2002. "Identification of Standard Auction Models," Econometrica, Econometric Society, vol. 70(6), pages 2107-2140, November.
    11. Luo, Yao & Xiao, Ruli, 2023. "Identification of auction models using order statistics," Journal of Econometrics, Elsevier, vol. 236(1).
    12. Hu, Yingyao & McAdams, David & Shum, Matthew, 2013. "Identification of first-price auctions with non-separable unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 174(2), pages 186-193.
    13. Yingyao Hu & Geert Ridder, 2012. "Estimation of nonlinear models with mismeasured regressors using marginal information," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 347-385, April.
    14. Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2023. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1265-1303.
    15. Aurore Delaigle & Peter Hall, 2016. "Methodology for non-parametric deconvolution when the error distribution is unknown," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 231-252, January.
    16. Jochmans, Koen & Weidner, Martin, 2024. "Inference On A Distribution From Noisy Draws," Econometric Theory, Cambridge University Press, vol. 40(1), pages 60-97, February.
    17. An, Yonghong & Hu, Yingyao, 2012. "Well-posedness of measurement error models for self-reported data," Journal of Econometrics, Elsevier, vol. 168(2), pages 259-269.
    18. Karun Adusumilli & Taisuke Otsu, 2015. "Nonparametric instrumental regression with errors in variables," STICERD - Econometrics Paper Series /2015/585, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    19. Corrado, L. & Weeks, M., 2010. "Identification Strategies in Survey Response Using Vignettes," Cambridge Working Papers in Economics 1031, Faculty of Economics, University of Cambridge.
    20. Barkley, Aaron & Groeger, Joachim R. & Miller, Robert A., 2021. "Bidding frictions in ascending auctions," Journal of Econometrics, Elsevier, vol. 223(2), pages 376-400.

    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:spr:sistpr:v:4:y:2001:i:2:p:181-198. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.