×

Nonparametric survival analysis with time-dependent covariate effects: A penalized partial likelihood approach. (English) Zbl 0708.62035

The goal of this paper is the estimation of the regression function \(\beta_ 0\) in a (generalized) Cox model, in which the hazard function has the representation \[ \lambda (t| z)=\lambda_ 0(t)\exp [\sum^{p}_{j=1}\beta_{oj}(t)z_ j]. \] The estimator results from maximization of an appropriate penalized partial likelihood. Consistency and (pointwise) asymptotic normality are shown. Proofs use methods from Sobolev-spaces and martingale theory.
Reviewer: W.Stute

MSC:

62G07 Density estimation
62G20 Asymptotic properties of nonparametric inference
62J02 General nonlinear regression
PDFBibTeX XMLCite
Full Text: DOI