IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v83y2013i5p1382-1387.html
   My bibliography  Save this article

Bias and bandwidth for local likelihood density estimation

Author

Listed:
  • Otneim, Håkon
  • Karlsen, Hans Arnfinn
  • Tjøstheim, Dag

Abstract

A local likelihood density estimator is shown to have asymptotic bias depending on the dimension of the local parameterization. Comparing with kernel estimation it is demonstrated using a variety of bandwidths that we may obtain as good and potentially even better estimates using local likelihood. Boundary effects are also examined.

Suggested Citation

  • Otneim, Håkon & Karlsen, Hans Arnfinn & Tjøstheim, Dag, 2013. "Bias and bandwidth for local likelihood density estimation," Statistics & Probability Letters, Elsevier, vol. 83(5), pages 1382-1387.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:5:p:1382-1387
    DOI: 10.1016/j.spl.2013.02.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715213000424
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2013.02.003?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. Peter Hall & Terence Tao, 2002. "Relative efficiencies of kernel and local likelihood density estimators," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 537-547, August.
    2. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
    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. Tata Subba Rao & Granville Tunnicliffe Wilson & Geir Drage Berentsen & Ricardo Cao & Mario Francisco-Fernández & Dag TjØstheim, 2017. "Some Properties of Local Gaussian Correlation and Other Nonlinear Dependence Measures," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 352-380, March.

    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. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    2. Lei Jiang & Esfandiar Maasoumi & Jiening Pan & Ke Wu, 2018. "A test of general asymmetric dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1026-1043, November.
    3. Georgios Bampinas & Theodore Panagiotidis, 2017. "Oil and stock markets before and after financial crises: A local Gaussian correlation approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(12), pages 1179-1204, December.
    4. Rodrigues, Clarissa Guimarães & Rios-Neto, Eduardo Luiz Gonçalves & de Xavier Pinto, Cristine Campos, 2013. "Changes in test scores distribution for students of the fourth grade in Brazil: A relative distribution analysis for the years 1997–2005," Economics of Education Review, Elsevier, vol. 34(C), pages 227-242.
    5. 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).
    6. Akimitsu Inoue, 2016. "Density estimation based on pointwise mutual information," Economics Bulletin, AccessEcon, vol. 36(2), pages 1138-1148.
    7. Lei Ming & Yao Shen & Shenggang Yang & Minyi Dong, 2022. "Contagion or flight‐to‐quality? The linkage between oil price and the US dollar based on the local Gaussian approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 722-750, April.
    8. Aleksy Leeuwenkamp & Wentao Hu, 2023. "New general dependence measures: construction, estimation and application to high-frequency stock returns," Papers 2309.00025, arXiv.org.
    9. Tobias Fissler & Marc-Oliver Pohle, 2023. "Generalised Covariances and Correlations," Papers 2307.03594, arXiv.org, revised Sep 2023.
    10. Panagiotis Avramidis, 2016. "Adaptive likelihood estimator of conditional variance function," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 132-151, March.
    11. Villa-Loaiza, Carlos & Taype-Huaman, Irvin & Benavides-Franco, Julián & Buenaventura-Vera, Guillermo & Carabalí-Mosquera, Jaime, 2023. "Does climate impact the relationship between the energy price and the stock market? The Colombian case," Applied Energy, Elsevier, vol. 336(C).
    12. Bampinas, Georgios & Panagiotidis, Theodore, 2024. "How would the war and the pandemic affect the stock and cryptocurrency cross-market linkages?," Research in International Business and Finance, Elsevier, vol. 70(PA).
    13. Lars Arne Jordanger & Dag Tjøstheim, 2023. "Local Gaussian Cross-Spectrum Analysis," Econometrics, MDPI, vol. 11(2), pages 1-27, April.
    14. Støve, Bård & Tjøstheim, Dag & Hufthammer, Karl Ove, 2014. "Using local Gaussian correlation in a nonlinear re-examination of financial contagion," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 62-82.
    15. Reinhold Heinlein & Gabriella D. Legrenzi & Scott M. R. Mahadeo, 2020. "Energy contagion in the COVID-19 crisis," Working Paper series 20-19, Rimini Centre for Economic Analysis.
    16. Davis, Richard & Drees, Holger & Segers, Johan & Warchol, Michal, 2018. "Inference on the tail process with application to financial time series modelling," LIDAM Discussion Papers ISBA 2018002, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. D.P. Amali Dassanayake & Igor Volobouev & A. Alexandre Trindade, 2017. "Local orthogonal polynomial expansion for density estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(4), pages 806-830, October.
    18. Elie Bouri & Rangan Gupta & Shixuan Wang, 2019. "Contagion between Stock and Real Estate Markets: International Evidence from a Local Gaussian Correlation Approach," Working Papers 201917, University of Pretoria, Department of Economics.
    19. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Ćmiel, Bogdan & Ledwina, Teresa, 2020. "Validation of association," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 55-67.

    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:eee:stapro:v:83:y:2013:i:5:p:1382-1387. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.