Semiparametic Estimation of Single-Index Hazard Functions Without Proportional Hazards  

Oleh:

Gorgens, Tue

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: The Econometrics Journal vol. 9 no. 1 (2006), page 1-22.
Topik: REGRESSION; semiparametric estimation; kernel regression; failure time analysis; survival analysis; duration analysis; competing risks; censoring
Fulltext: 1.pdf (193.17KB)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: EE39.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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This research develops a semiparametric kernel - based estimator of hazard functions which does not assume proportional hazards. The maintained assumption is that the hazard functions depend on regressors only through a linear index. The estimator permits both discrete and continuous regressors, both discrete and continuous failure times, and can be applied to right - censored data and to multiple - risks data, in which case the hazard functions are risk - specific. The estimator is root - n consistent and asymptotically normally distributed. The estimator performs well in Monte Carlo experiments.

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