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Nonlinear Regression With Censored Data

Summary: [This abstract is based on the authors' abstract.]A new method is proposed for estimating the parameters of the nonlinear censored regression model 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, and the estimator is compared through simulations with a previously established estimator. Both methods are applied to a fatigue life dataset of strain-controlled materials.

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  • Topics: Data Quality
  • Keywords: Bootstrap methods,Censored data,Kernel density estimates,Least squares,Life testing,Nonparametric methods,Regression analysis
  • Author: Heuchenne, Cedric; Van Keilegom, Ingrid
  • Journal: Technometrics