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Estimating Multiplicative and Additive Hazard Functions by Kernel Methods


Author Info

  • Linton, Oliver B.

    (Department of Economics)

  • Perch Nielsen, Jens


  • Van de Geer, Sara

    (Mathematical Institute)


We propose new procedures for estimating the univariate quantities of interest in both additive and multiplicative nonparametric marker dependent hazard models. We work with a full counting process framework that allows for left truncation and right censoring. Our procedures are based on kernels and on the idea of marginal integration. we provide a central limit theorem for our estimator.

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Bibliographic Info

Paper provided by University of Aarhus, Aarhus School of Business, Department of Business Studies in its series Finance Working Papers with number 01-2.

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Length: 36 pages
Date of creation: 21 Feb 2001
Date of revision:
Handle: RePEc:hhb:aarfin:2001_002

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Postal: The Aarhus School of Business, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark
Fax: + 45 86 15 19 43
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Related research

Keywords: Additive Model; Censoring; Kernel; Proportional Hazards; Survival Analysis;

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References listed on IDEAS
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  1. Enno Mammen & Oliver Linton & J Nielsen, 2000. "The existence and asymptotic properties of a backfitting projection algorithm under weak conditions," LSE Research Online Documents on Economics 2315, London School of Economics and Political Science, LSE Library.
  2. Oliver LINTON, . "Kernel estimation in a nonparametric marker dependent Hazard Model," Statistic und Oekonometrie 9313, Humboldt Universitaet Berlin.
  3. Felipe, Angie & Guillen, Montserrat & Perch Nielsen, Jens, 2000. "Longevity Studies Based on Kernel Hazard Estimation," Finance Working Papers 00-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.
  4. Masry, Elias, 1996. "Multivariate regression estimation local polynomial fitting for time series," Stochastic Processes and their Applications, Elsevier, vol. 65(1), pages 81-101, December.
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Cited by:
  1. Woocheol Kim & Oliver Linton, 2004. "A local instrumental variable estimation method for generalized additive volatility models," LSE Research Online Documents on Economics 24758, London School of Economics and Political Science, LSE Library.
  2. Gregory Connor & Oliver Linton & Matthias Hagmann, 2007. "Efficient Estimation of a Semiparametric Characteristic-Based Factor Model of Security Returns," FMG Discussion Papers dp599, Financial Markets Group.
  3. Toshio Honda, 2005. "Estimation in additive cox models by marginal integration," Annals of the Institute of Statistical Mathematics, Springer, vol. 57(3), pages 403-423, September.


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