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arXiv · 1707.04622

Smooth backfitting of proportional hazards with multiplicative components

Munir Hiabu·Enno Mammen·Maria Dolores Martinez-Miranda·Jens Perch Nielsen
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Abstract

Smooth backfitting has proven to have a number of theoretical and practical advantages in structured regression. Smooth backfitting projects the data down onto the structured space of interest providing a direct link between data and estimator. This paper introduces the ideas of smooth backfitting to survival analysis in a proportional hazard model, where we assume an underlying conditional hazard with multiplicative components. We develop asymptotic theory for the estimator and we use the smooth backfitter in a practical application, where we extend recent advances of in-sample forecasting methodology by allowing more information to be incorporated, while still obeying the structured requirements of in-sample forecasting.

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Munir Hiabu, Enno Mammen, Maria Dolores Martinez-Miranda, Jens Perch Nielsen. 2017-07-14. Smooth backfitting of proportional hazards with multiplicative components. https://arxiv.org/abs/1707.04622

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