IDEAS home Printed from https://ideas.repec.org/a/spr/metrik/v79y2016i2p195-220.html

Information bounds for nonparametric estimators of L-functionals and survival functionals under censored data

Author

Listed:
  • Arnold Janssen

  • Andreas Knoch

Abstract

In the present paper we derive lower asymptotic information bounds of Cramér-Rao type for estimators of nonparametric statistical functionals. The results are based on dense differentiability and dense regularity concepts which lead to weak assumptions. As explicit examples L-estimators are treated. In addition a new rapid method for the treatment of survival functionals under randomly right censored data is presented. For instance, for the famous Kaplan-Meier and Nelson-Aalen estimators, our information bound is just the lower bound obtained earlier in the literature. Copyright Springer-Verlag Berlin Heidelberg 2016

Suggested Citation

  • Arnold Janssen & Andreas Knoch, 2016. "Information bounds for nonparametric estimators of L-functionals and survival functionals under censored data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(2), pages 195-220, February.
  • Handle: RePEc:spr:metrik:v:79:y:2016:i:2:p:195-220
    DOI: 10.1007/s00184-015-0551-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00184-015-0551-y
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s00184-015-0551-y?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Arnold Janssen & Stefan Wellek, 2010. "Exact linear rank tests for two‐sample equivalence problems with continuous data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(4), pages 482-504, November.
    2. Beutner, Eric & Zähle, Henryk, 2010. "A modified functional delta method and its application to the estimation of risk functionals," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2452-2463, November.
    3. J. Pfanzagl, 2003. "Asymptotic bounds for estimators without limit distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(1), pages 95-110, March.
    4. R.D. Gill, 1980. "Censoring and Stochastic Integrals," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 34(2), pages 124-124, June.
    5. A. Janssen, 1989. "Local asymptotic normality for randomly censored models with applications to rank tests," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 43(2), pages 109-125, June.
    6. Einmahl, J.H.J., 1996. "A short and elementary proof of the main Bahadur-Kiefer theorem," Other publications TiSEM bd980f38-c118-4174-9816-8, Tilburg University, School of Economics and Management.
    7. Janssen, Arnold, 1994. "On local odds and hazard rate models in survival analysis," Statistics & Probability Letters, Elsevier, vol. 20(5), pages 355-365, August.
    8. Janssen, Arnold, 2003. "A nonparametric Cramer-Rao inequality for estimators of statistical functionals," Statistics & Probability Letters, Elsevier, vol. 64(4), pages 347-358, October.
    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. Michael Brendel & Arnold Janssen & Claus-Dieter Mayer & Markus Pauly, 2014. "Weighted Logrank Permutation Tests for Randomly Right Censored Life Science Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 742-761, September.
    2. Heck-Boldebuck D. & Liese F. & Neuhaus G., 2002. "Optimal Nonparametric Tests For Truncated Data," Statistics & Risk Modeling, De Gruyter, vol. 20(1-4), pages 111-136, April.
    3. Buchsteiner, Jannis, 2015. "Weak convergence of the weighted sequential empirical process of some long-range dependent data," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 170-179.
    4. Soren Bettels & Stefan Weber, 2024. "An Integrated Approach to Importance Sampling and Machine Learning for Efficient Monte Carlo Estimation of Distortion Risk Measures in Black Box Models," Papers 2408.02401, arXiv.org, revised Aug 2025.
    5. Lu, Xuewen & Burke, M.D., 2005. "Censored multiple regression by the method of average derivatives," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 182-205, July.
    6. Janurová, Kateřina & Briš, Radim, 2014. "A nonparametric approach to medical survival data: Uncertainty in the context of risk in mortality analysis," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 145-152.
    7. John T. O'Gorman & Michael G. Akritas, 2001. "Nonparametric Models and Methods for Designs with Dependent Censored Data: Part I," Biometrics, The International Biometric Society, vol. 57(1), pages 88-95, March.
    8. Erica Brittain & Dean Follmann & Song Yang, 2008. "Dynamic Comparison of Kaplan–Meier Proportions: Monitoring a Randomized Clinical Trial with a Long-Term Binary Endpoint," Biometrics, The International Biometric Society, vol. 64(1), pages 189-197, March.
    9. Xiaofeng Lv & Gupeng Zhang & Guangyu Ren, 2017. "Gini index estimation for lifetime data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 275-304, April.
    10. Martin Wells & Ram Tiwari, 1994. "Bootstrapping a Bayes estimator of a survival function with censored data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(3), pages 487-495, September.
    11. Anil K. Bera & Malabika Koley, 2023. "A History of the Delta Method and Some New Results," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 272-306, November.
    12. Beare, Brendan K. & Shi, Xiaoxia, 2019. "An improved bootstrap test of density ratio ordering," Econometrics and Statistics, Elsevier, vol. 10(C), pages 9-26.
    13. Chen, Xiaohong & Fan, Yanqin & Pouzo, Demian & Ying, Zhiliang, 2010. "Estimation and model selection of semiparametric multivariate survival functions under general censorship," Journal of Econometrics, Elsevier, vol. 157(1), pages 129-142, July.
    14. Phadia, Eswar G. & Shao, Peter Yi-Shi, 1999. "Exact moments of the product limit estimator," Statistics & Probability Letters, Elsevier, vol. 41(3), pages 277-286, February.
    15. Daniel Scharfstein & James M. Robins & Wesley Eddings & Andrea Rotnitzky, 2001. "Inference in Randomized Studies with Informative Censoring and Discrete Time-to-Event Endpoints," Biometrics, The International Biometric Society, vol. 57(2), pages 404-413, June.
    16. Yi Wu & Wei Yu & Xuejun Wang, 2022. "Strong representations of the Kaplan–Meier estimator and hazard estimator with censored widely orthant dependent data," Computational Statistics, Springer, vol. 37(1), pages 383-402, March.
    17. Michael Weba & Nora Dörmann, 2017. "Application of the delta method to functions of the sample mean when observations are dependent," Statistical Papers, Springer, vol. 58(4), pages 957-986, December.
    18. Hua Liang & Yong Zhou, 2008. "Semiparametric Inference for ROC Curves with Censoring," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(2), pages 212-227, June.
    19. Han-Ying Liang & Jacobo Uña-Álvarez, 2011. "Asymptotic properties of conditional quantile estimator for censored dependent observations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(2), pages 267-289, April.
    20. Ganesh B. Malla, 2022. "A Monte Carlo Simulation Comparison of Some Nonparametric Survival Functions for Incomplete Data," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 14(5), pages 1-1, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:metrik:v:79:y:2016:i:2:p:195-220. 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.