Reference : Nonlinear regression with censored data
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Mathematics
http://hdl.handle.net/2268/11279
Nonlinear regression with censored data
English
Heuchenne, Cédric mailto [Université de Liège - ULg > HEC - Ecole de gestion de l'ULg > Statistique appliquée à la gestion et à l'économie >]
Van Keilegom, Ingrid [> > > >]
2007
Technometrics
American Statistical Association
49
1
34-44
Yes (verified by ORBi)
International
0040-1706
[en] bootstrap ; fatigue life data ; kernel method ; least squares estimation ; nonparametric regression ; right censoring ; survival analysis ; bandwidth selection
[en] Suppose that the random vector (X, Y) satisfies the regression model Y = m(X) + sigma(X)epsilon, where m(.) = E(Y vertical bar.) belongs to some parametric class (m(theta)(.):theta is an element of Theta) of regression functions, sigma(2)(.) = var(Y vertical bar.) is unknown, and e is independent of X. The response Y is subject to random right censoring, and the covariate X is completely observed. A new estimation procedure for the true, unknown parameter vector theta(0) is proposed that extends the classical least squares procedure for nonlinear regression to the case where the response is subject to censoring. The consistency and asymptotic normality of the proposed estimator are established. The estimator is compared through simulations with an estimator proposed by Stute in 1999, and both methods are also applied to a fatigue life dataset of strain-controlled materials.
http://hdl.handle.net/2268/11279
10.1198/004017006000000417

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