IDEAS home Printed from https://ideas.repec.org/a/spr/aistmt/v45y1993i2p317-329.html
   My bibliography  Save this article

A smoothed bootstrap estimator for a studentized sample quantile

Author

Listed:
  • Daniel Janas

Abstract

No abstract is available for this item.

Suggested Citation

  • Daniel Janas, 1993. "A smoothed bootstrap estimator for a studentized sample quantile," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(2), pages 317-329, June.
    • Handle: RePEc:spr:aistmt:v:45:y:1993:i:2:p:317-329
    DOI: 10.1007/BF00775817
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF00775817
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF00775817?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. Jones, M. C., 1990. "The performance of kernel density functions in kernel distribution function estimation," Statistics & Probability Letters, Elsevier, vol. 9(2), pages 129-132, February.
    2. M. Falk, 1983. "Relative efficiency and deficiency of kernel type estimators of smooth distribution functions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 37(2), pages 73-83, June.
    3. Falk, Michael, 1990. "Weak convergence of the maximum error of the bootstrap quantile estimate," Statistics & Probability Letters, Elsevier, vol. 10(4), pages 301-305, September.
    4. Hall, Peter & Martin, Michael A., 1991. "On the error incurred using the bootstrap variance estimate when constructing confidence intervals for quantiles," Journal of Multivariate Analysis, Elsevier, vol. 38(1), pages 70-81, July.
    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. Joel L. Horowitz, 1998. "Bootstrap Methods for Median Regression Models," Econometrica, Econometric Society, vol. 66(6), pages 1327-1352, November.
    2. David M. Kaplan & Matt Goldman, 2013. "IDEAL Quantile Inference via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1315, Department of Economics, University of Missouri.
    3. Gabriel Montes Rojas & Andrés Sebastián Mena, 2020. "Density estimation using bootstrap quantile variance and quantile-mean covariance," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2020-50, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    4. Yoshihiko Maesono & Spiridon Penev, 2013. "Improved confidence intervals for quantiles," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 167-189, February.

    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. Bouzebda, Salim & Slaoui, Yousri, 2022. "Nonparametric recursive method for moment generating function kernel-type estimators," Statistics & Probability Letters, Elsevier, vol. 184(C).
    2. Alexandre Leblanc, 2012. "On estimating distribution functions using Bernstein polynomials," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(5), pages 919-943, October.
    3. Roussas, George G., 1995. "Asymptotic normality of a smooth estimate of a random field distribution function under association," Statistics & Probability Letters, Elsevier, vol. 24(1), pages 77-90, July.
    4. Falk, Michael & Reiss, Rolf-Dieter, 2003. "Efficient estimators and LAN in canonical bivariate POT models," Journal of Multivariate Analysis, Elsevier, vol. 84(1), pages 190-207, January.
    5. Jungmin An & Dong-Kwan Kim & Jinyeong Lee & Sung-Kwan Joo, 2021. "Least Squares Monte Carlo Simulation-Based Decision-Making Method for Photovoltaic Investment in Korea," Sustainability, MDPI, vol. 13(19), pages 1-14, September.
    6. Miguel Arcones, 2003. "On the asymptotic accuracy of the bootstrap under arbitrary resampling size," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(3), pages 563-583, September.
    7. Stewart, Mark B., 2011. "Quantile estimates of counterfactual distribution shifts and the impact of minimum wage increases on the wage distribution," Economic Research Papers 270766, University of Warwick - Department of Economics.
    8. Janssen, Paul & Swanepoel, Jan & Veraverbeke, Noël, 2001. "Modified bootstrap consistency rates for U-quantiles," Statistics & Probability Letters, Elsevier, vol. 54(3), pages 261-268, October.
    9. Hussein Khraibani & Bilal Nehme & Olivier Strauss, 2018. "Interval Estimation of Value-at-Risk Based on Nonparametric Models," Econometrics, MDPI, vol. 6(4), pages 1-30, December.
    10. Alevizos, Filippos & Bagkavos, Dimitrios & Ioannides, Dimitrios, 2019. "Efficient estimation of a distribution function based on censored data," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 359-364.
    11. Minglu Ma & Qiang Wang, 2022. "Assessment and Forecast of Green Total Factor Energy Efficiency in the Yellow River Basin—A Perspective Distinguishing the Upper, Middle and Lower Stream," Sustainability, MDPI, vol. 14(5), pages 1-23, February.
    12. Shingo Shirahata & In-Sun Chu, 1992. "Integrated squared error of kernel-type estimator of distribution function," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 44(3), pages 579-591, September.
    13. Ariane Hanebeck & Bernhard Klar, 2021. "Smooth distribution function estimation for lifetime distributions using Szasz–Mirakyan operators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(6), pages 1229-1247, December.
    14. Donald W.K. Andrews & Moshe Buchinsky, 1997. "On the Number of Bootstrap Repetitions for Bootstrap Standard Errors, Confidence Intervals, and Tests," Cowles Foundation Discussion Papers 1141R, Cowles Foundation for Research in Economics, Yale University.
    15. Ralescu, Stefan S. & Puri, Madan L., 1996. "Weak convergence of sequences of first passage processes and applications," Stochastic Processes and their Applications, Elsevier, vol. 62(2), pages 327-345, July.
    16. Funke, Benedikt & Palmes, Christian, 2017. "A note on estimating cumulative distribution functions by the use of convolution power kernels," Statistics & Probability Letters, Elsevier, vol. 121(C), pages 90-98.
    17. Mammitzsch Volker, 2007. "Optimal kernels," Statistics & Risk Modeling, De Gruyter, vol. 25(2/2007), pages 1-20, April.
    18. Arup Bose & Santanu Dutta, 2022. "Kernel based estimation of the distribution function for length biased data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(3), pages 269-287, April.
    19. Lloyd, Chris J. & Yong, Zhou, 1999. "Kernel estimators of the ROC curve are better than empirical," Statistics & Probability Letters, Elsevier, vol. 44(3), pages 221-228, September.
    20. Shan Luo & Gengsheng Qin, 2017. "New non-parametric inferences for low-income proportions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(3), pages 599-626, June.

    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:aistmt:v:45:y:1993:i:2:p:317-329. 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.