Smooth backfitting of proportional hazards

• Verfasst von: Hiabu, Munir [VerfasserIn]
• Verfasst von: Mammen, Enno [VerfasserIn]
• Verfasst von: Martinez Miranda, Maria Dolores [VerfasserIn]
• Verfasst von: Nielsen, Jens Perch [VerfasserIn]
• Titel: Smooth backfitting of proportional hazards
• Titelzusatz: anew approach projecting survival data
• Verf.angabe: Munir Hiabu, Enno Mammen, Maria Dolores Martinez-Miranda, Jens Perch Nielsen
• Fussnoten: Gesehen am 22.01.2018
• Titel Quelle: Enthalten in: De.arxiv.org
• Jahr Quelle: 2017
• Band/Heft Quelle: (2017) Artikel-Nummer 1707.04622v1, 32 Seiten
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1567398901

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.