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On penalized likelihood estimation for a non-proportional hazards regression model

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  • Devarajan, Karthik
  • Ebrahimi, Nader

Abstract

In this paper, a semi-parametric generalization of the Cox model that permits crossing hazard curves is described. A theoretical framework for estimation in this model is developed based on penalized likelihood methods. It is shown that the optimal solution to the baseline hazard, baseline cumulative hazard and their ratio are hyperbolic splines with knots at the distinct failure times.

Suggested Citation

  • Devarajan, Karthik & Ebrahimi, Nader, 2013. "On penalized likelihood estimation for a non-proportional hazards regression model," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1703-1710.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:7:p:1703-1710
    DOI: 10.1016/j.spl.2013.03.007
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    References listed on IDEAS

    as
    1. Fushing Hsieh, 2001. "On heteroscedastic hazards regression models: theory and application," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 63-79.
    2. Devarajan, Karthik & Ebrahimi, Nader, 2011. "A semi-parametric generalization of the Cox proportional hazards regression model: Inference and applications," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 667-676, January.
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