• Bernoulli
  • Volume 23, Number 4B (2017), 3437-3468.

Efficiency and bootstrap in the promotion time cure model

François Portier, Anouar El Ghouch, and Ingrid Van Keilegom

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In this paper, we consider a semiparametric promotion time cure model and study the asymptotic properties of its nonparametric maximum likelihood estimator (NPMLE). First, by relying on a profile likelihood approach, we show that the NPMLE may be computed by a single maximization over a set whose dimension equals the dimension of the covariates plus one. Next, using $Z$-estimation theory for semiparametric models, we derive the asymptotics of both the parametric and nonparametric components of the model and show their efficiency. We also express the asymptotic variance of the estimator of the parametric component. Since the variance is difficult to estimate, we develop a weighted bootstrap procedure that allows for a consistent approximation of the asymptotic law of the estimators. As in the Cox model, it turns out that suitable tools are the martingale theory for counting processes and the infinite dimensional $Z$-estimation theory. Finally, by means of simulations, we show the accuracy of the bootstrap approximation.

Article information

Bernoulli, Volume 23, Number 4B (2017), 3437-3468.

Received: March 2015
Revised: January 2016
First available in Project Euclid: 23 May 2017

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Zentralblatt MATH identifier

asymptotic inference bootstrap Cox model promotion time cure model semiparametric efficiency


Portier, François; El Ghouch, Anouar; Van Keilegom, Ingrid. Efficiency and bootstrap in the promotion time cure model. Bernoulli 23 (2017), no. 4B, 3437--3468. doi:10.3150/16-BEJ852.

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