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hal-01161820v1  Communication dans un congrès
Eric BeutnerLaurent BordesLaurent DoyenFailure of the profile likelihood method for semi-parametric virtual age models
MMR 2015 - 9th International Conference on Mathematical Methods in Reliability, Jun 2015, Tokyo, Japan
hal-01240355v1  Communication dans un congrès
Eric BeutnerLaurent BordesLaurent DoyenVirtual age model with unknown event effects
IV WASA - Workshop on Survival Analysis and Applications, Nov 2015, Belo Horizonte, Brazil
hal-01189171v1  Communication dans un congrès
Eric BeutnerLaurent BordesLaurent DoyenOn a large class of models for recurrent events for which profile likelihood inference fails
European Meeting of Statisticians, Jul 2015, Amtesdam, Netherlands
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hal-01478523v1  Communication dans un congrès
Laurent BordesDidier ChauveauStochastic EM-like Algorithms for Fitting Finite Mixture of Lifetime Regression Models Under Right Censoring
Alexandria, VA: American Statistical Association. Joint Statistical Meeting 2016, Jul 2016, Chicago, United States. JSM Proceedings, Section on Nonparametric Statistics, pp.1735-1746, 2016, <https://ww2.amstat.org/meetings/jsm/2016/>
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hal-00501865v3  Article dans une revue
Laurent BordesJean-Yves DauxoisPierre JolySemiparametric inference of competing risks data with additive hazards and missing cause of failure under MCAR or MAR assumptions
Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2014, 8, pp.41-95. <10.1214/14-EJS876>
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hal-00018493v1  Article dans une revue
Laurent BordesDidier ChauveauPierre VandekerkhoveA Stochastic EM algorithm for a semiparametric mixture model
Computational Statistics and Data Analysis, Elsevier, 2007, 51, pp.5429-5443. <10.1016/j.csda.2006.08.015>
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hal-00174725v1  Article dans une revue
Laurent BordesPierre VandekerkhoveSEMIPARAMETRIC TWO-COMPONENT MIXTURE MODEL WITH A KNOWN COMPONENT: A CLASS OF ASYMPTOTICALLY NORMAL ESTIMATORS
Mathematical Methods of Statistics, Allerton Press, Springer (link), 2010, 19 (1), pp.22-41. <10.3103/s1066530710010023>