Smooth backfitting of proportional hazards with multiplicative components
Statistics Theory
2020-02-07 v2 Statistics Theory
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.
Keywords
Cite
@article{arxiv.1707.04622,
title = {Smooth backfitting of proportional hazards with multiplicative components},
author = {Munir Hiabu and Enno Mammen and Maria Dolores Martinez-Miranda and Jens Perch Nielsen},
journal= {arXiv preprint arXiv:1707.04622},
year = {2020}
}