IDEAS home Printed from https://ideas.repec.org/a/spr/aistmt/v64y2012i1p167-192.html
   My bibliography  Save this article

Multivariate density estimation using dimension reducing information and tail flattening transformations for truncated or censored data

Author

Listed:
  • Tine Buch-Kromann
  • Jens Nielsen

Abstract

No abstract is available for this item.

Suggested Citation

  • Tine Buch-Kromann & Jens Nielsen, 2012. "Multivariate density estimation using dimension reducing information and tail flattening transformations for truncated or censored data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(1), pages 167-192, February.
    • Handle: RePEc:spr:aistmt:v:64:y:2012:i:1:p:167-192
    DOI: 10.1007/s10463-010-0313-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10463-010-0313-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10463-010-0313-6?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. Dimitrios Bagkavos, 2008. "Transformations in hazard rate estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(8), pages 721-738.
    2. Bolance, Catalina & Guillen, Montserrat & Nielsen, Jens Perch, 2003. "Kernel density estimation of actuarial loss functions," Insurance: Mathematics and Economics, Elsevier, vol. 32(1), pages 19-36, February.
    3. Montserrat Guillen & Jim Gustafsson & Jens Perch Nielsen & Paul Pritchard, 2007. "Using External Data in Operational Risk," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 32(2), pages 178-189, April.
    4. Enno Mammen & Jens Perch Nielsen, 2007. "A General Approach to the Predictability Issue in Survival Analysis with Applications," Biometrika, Biometrika Trust, vol. 94(4), pages 873-892.
    5. Jens Perch Nielsen & Carsten Tanggaard, 2001. "Boundary and Bias Correction in Kernel Hazard Estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(4), pages 675-698, December.
    6. Bolancé, Catalina & Guillén, Montserrat & Nielsen, Jens Perch, 2008. "Inverse beta transformation in kernel density estimation," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1757-1764, September.
    7. Clements A. & Hurn S. & Lindsay K., 2003. "Mobius-Like Mappings and Their Use in Kernel Density Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 993-1000, January.
    8. Ingrid Van Keilegom & Noël Veraverbeke, 2001. "Hazard Rate Estimation in Nonparametric Regression with Censored Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(4), pages 730-745, December.
    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. Gámiz Pérez, M. Luz & Martínez Miranda, María Dolores & Nielsen, Jens Perch, 2013. "Smoothing survival densities in practice," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 368-382.

    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. Buch-Kromann, Tine & Guillén, Montserrat & Linton, Oliver & Nielsen, Jens Perch, 2011. "Multivariate density estimation using dimension reducing information and tail flattening transformations," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 99-110, January.
    2. María Luz Gámiz & Enno Mammen & María Dolores Martínez Miranda & Jens Perch Nielsen, 2016. "Double one-sided cross-validation of local linear hazards," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 755-779, September.
    3. Catalina Bolance & Montserrat Guillen & David Pitt, 2014. "Non-parametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers 2014-01, Universitat de Barcelona, UB Riskcenter.
    4. David Pitt & Montserrat Guillen & Catalina Bolancé, 2011. "Estimation of Parametric and Nonparametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers XREAP2011-06, Xarxa de Referència en Economia Aplicada (XREAP), revised Jun 2011.
    5. David Pitt & Montserrat Guillén, 2010. "An introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions," Working Papers XREAP2010-03, Xarxa de Referència en Economia Aplicada (XREAP), revised Mar 2010.
    6. Ramon Alemany & Catalina Bolancé & Montserrat Guillén, 2012. "Nonparametric estimation of Value-at-Risk," Working Papers XREAP2012-19, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2012.
    7. Bolancé, Catalina & Guillén, Montserrat & Nielsen, Jens Perch, 2008. "Inverse beta transformation in kernel density estimation," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1757-1764, September.
    8. Ramon ALEMANY & Catalina BOLANCÉ & Montserrat GUILLÉN & Alemar E. PADILLA-BARRETO, 2016. "Combining Parametric And Non-Parametric Methods To Compute Value-At-Risk," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 61-74.
    9. Alemany, Ramon & Bolancé, Catalina & Guillén, Montserrat, 2013. "A nonparametric approach to calculating value-at-risk," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 255-262.
    10. J. M. Vilar & R. Cao & M. C. Ausin & C. Gonzalez-Fragueiro, 2009. "Nonparametric analysis of aggregate loss models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(2), pages 149-166.
    11. Spierdijk, Laura, 2008. "Nonparametric conditional hazard rate estimation: A local linear approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2419-2434, January.
    12. van den Berg, Gerard J. & Janys, Lena & Mammen, Enno & Nielsen, Jens P., 2014. "A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models," IZA Discussion Papers 8339, Institute of Labor Economics (IZA).
    13. Bolance, Catalina & Guillen, Montserrat & Pelican, Elena & Vernic, Raluca, 2008. "Skewed bivariate models and nonparametric estimation for the CTE risk measure," Insurance: Mathematics and Economics, Elsevier, vol. 43(3), pages 386-393, December.
    14. Ramon Alemany & Catalina Bolance & Montserrat Guillen, 2014. "Accounting for severity of risk when pricing insurance products," Working Papers 2014-05, Universitat de Barcelona, UB Riskcenter.
    15. Juxia Xiao & Xu Li & Jianhong Shi, 2019. "Local linear smoothers using inverse Gaussian regression," Statistical Papers, Springer, vol. 60(4), pages 1225-1253, August.
    16. Catalina Bolancé & Montserrat Guillen, 2021. "Nonparametric Estimation of Extreme Quantiles with an Application to Longevity Risk," Risks, MDPI, vol. 9(4), pages 1-23, April.
    17. Janys, Lena, 2017. "A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168077, Verein für Socialpolitik / German Economic Association.
    18. van den Berg, Gerard. J. & Janys, Lena & Mammen, Enno & Nielsen, Jens Perch, 2021. "A general semiparametric approach to inference with marker-dependent hazard rate models," Journal of Econometrics, Elsevier, vol. 221(1), pages 43-67.
    19. Jeon, Yongho & Kim, Joseph H.T., 2013. "A gamma kernel density estimation for insurance loss data," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 569-579.
    20. Hirukawa, Masayuki, 2010. "Nonparametric multiplicative bias correction for kernel-type density estimation on the unit interval," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 473-495, February.

    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:64:y:2012:i:1:p:167-192. 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.