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Extremum Sieve Estimation in k-out-of-n Systems

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  • Tatiana Komarova

Abstract

The paper considers nonparametric estimation of absolutely continuous distribution functions of lifetimes of non-identical components in k-out-of-n systems from the observed "autopsy" data. In economics,ascending "button" or "clock" auctions with n heterogeneous bidders present 2-out-of-n systems. Classical competing risks models are examples of n-out-of-n systems. Under weak conditions on the underlying distributions the estimation problem is shown to be well-posed and the suggested extremum sieve estimator is proven to be consistent. The paper illustrates the suggested estimation method by using sieve spaces of Bernstein polynomials which allow an easy implementation of constraints on the monotonicity of estimated distribution functions.

Suggested Citation

  • Tatiana Komarova, 2013. "Extremum Sieve Estimation in k-out-of-n Systems," STICERD - Econometrics Paper Series 564, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  • Handle: RePEc:cep:stiecm:564
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    File URL: https://sticerd.lse.ac.uk/dps/em/em564.pdf
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    References listed on IDEAS

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    1. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    2. Whitney K. Newey & James L. Powell, 2003. "Instrumental Variable Estimation of Nonparametric Models," Econometrica, Econometric Society, vol. 71(5), pages 1565-1578, September.
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    More about this item

    Keywords

    k-out-of-n systems; competing risks; sieve estimation; Bernstein polynomials;
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