IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v36y2021i1d10.1007_s00180-020-01007-w.html
   My bibliography  Save this article

Two generalized nonparametric methods for estimating like densities

Author

Listed:
  • Zongyuan Shang

    (University of Guelph)

  • Alan Ker

    (University of Guelph)

Abstract

This article presents two generalized nonparametric methods for estimating multiple, possibly like, densities. The first generalization contains the Nadaraya–Watson estimator, the Jones et al. (Biometrika 82(2):327–338, 1995) bias reduction estimator, and Ker (Stat Probab Lett 117:23–30, 2016) possibly similar estimator as special cases. The second generalization contains the Nadaraya–Watson estimator, Ker (2016) possibly similar estimator, and the conditional density estimator of Hall et al. (J Am Stat Assoc 99(468):1015–1026, 2004) as special cases. The generalizations do not require knowledge of the form or extent of likeness between the unknown densities; an attractive feature in empirical applications. Numerical simulations demonstrate that the two proposed generalizations lead to significant efficiency gains.

Suggested Citation

  • Zongyuan Shang & Alan Ker, 2021. "Two generalized nonparametric methods for estimating like densities," Computational Statistics, Springer, vol. 36(1), pages 113-126, March.
    • Handle: RePEc:spr:compst:v:36:y:2021:i:1:d:10.1007_s00180-020-01007-w
    DOI: 10.1007/s00180-020-01007-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-020-01007-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00180-020-01007-w?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. Racine, Jeffrey S. & Ker, Alan P., 2006. "Rating Crop Insurance Policies with Efficient Nonparametric Estimators that Admit Mixed Data Types," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 31(1), pages 1-13, April.
    2. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
    3. Ker, Alan P. & Ergün, A.T., 2005. "Empirical Bayes nonparametric kernel density estimation," Statistics & Probability Letters, Elsevier, vol. 75(4), pages 315-324, December.
    4. Alan P. Ker & Yong Liu, 2017. "Bayesian model averaging of possibly similar nonparametric densities," Computational Statistics, Springer, vol. 32(1), pages 349-365, March.
    5. Ker, Alan P., 2016. "Nonparametric estimation of possibly similar densities," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 23-30.
    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. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.
    2. Kemp, Gordon C.R. & Santos Silva, J.M.C., 2012. "Regression towards the mode," Journal of Econometrics, Elsevier, vol. 170(1), pages 92-101.
    3. Degl’Innocenti, Marta & Matousek, Roman & Sevic, Zeljko & Tzeremes, Nickolaos G., 2017. "Bank efficiency and financial centres: Does geographical location matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 188-198.
    4. George Halkos & Roman Matousek & Nickolaos Tzeremes, 2016. "Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 47-77, January.
    5. Qi Li & Juan Lin & Jeffrey S. Racine, 2013. "Optimal Bandwidth Selection for Nonparametric Conditional Distribution and Quantile Functions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 57-65, January.
    6. Michael S. Delgado & Daniel J. Henderson & Christopher F. Parmeter, 2014. "Does Education Matter for Economic Growth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(3), pages 334-359, June.
    7. Jean Pierre Huiban & Camille Mastromarco & Antonio Musolesi & Michel Simioni, 2016. "The impact of pollution abatement investments on production technology: new insights from frontier analysis," Working Papers hal-01512154, HAL.
    8. Cong Li & Qi Li & Jeffrey Racine & DAIQIANG ZHANG, 2017. "Optimal Model Averaging Of Varying Coefficient Models," Department of Economics Working Papers 2017-01, McMaster University.
    9. Nolwenn Roudaut & Anne Vanhems, 2012. "Explaining firms efficiency in the Ivorian manufacturing sector: a robust nonparametric approach," Journal of Productivity Analysis, Springer, vol. 37(2), pages 155-169, April.
    10. Yong Liu & A. Ford Ramsey, 2023. "Incorporating historical weather information in crop insurance rating," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(2), pages 546-575, March.
    11. Olmo, José & Sanso-Navarro, Marcos, 2012. "Forecasting the performance of hedge fund styles," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2351-2365.
    12. Jeff Racine & Qi Li & Xi Zhu, 2004. "Kernel Estimation of Multivariate Conditional Distributions," Annals of Economics and Finance, Society for AEF, vol. 5(2), pages 211-235, November.
    13. Chen, Xirong & Li, Degui & Li, Qi & Li, Zheng, 2019. "Nonparametric estimation of conditional quantile functions in the presence of irrelevant covariates," Journal of Econometrics, Elsevier, vol. 212(2), pages 433-450.
    14. Bontemps, Christophe & Racine, Jeffrey S. & Simioni, Michel, 2009. "Nonparametric vs Parametric Binary Choice Models: An Empirical Investigation," TSE Working Papers 09-126, Toulouse School of Economics (TSE).
    15. Jianqing Fan, 2004. "A selective overview of nonparametric methods in financial econometrics," Papers math/0411034, arXiv.org.
    16. Bampinas, Georgios & Panagiotidis, Theodore & Politsidis, Panagiotis N., 2023. "Sovereign bond and CDS market contagion: A story from the Eurozone crisis," Journal of International Money and Finance, Elsevier, vol. 137(C).
    17. George Halkos & Nickolaos Tzeremes, 2012. "Measuring German regions’ environmental efficiency: a directional distance function approach," Letters in Spatial and Resource Sciences, Springer, vol. 5(1), pages 7-16, March.
    18. Daniel J. Henderson & Alexandre Olbrecht & Solomon W. Polachek, 2006. "Do Former College Athletes Earn More at Work?: A Nonparametric Assessment," Journal of Human Resources, University of Wisconsin Press, vol. 41(3).
    19. João Amador & Sónia Cabral & José Maria, 2010. "What can we learn from the distribution of trade patterns?," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 9(2), pages 77-95, August.
    20. P. Čížek & S. Sadikoglu, 2018. "Bias-corrected quantile regression estimation of censored regression models," Statistical Papers, Springer, vol. 59(1), pages 215-247, March.

    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:compst:v:36:y:2021:i:1:d:10.1007_s00180-020-01007-w. 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.