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EM and Stochastic EM algorithms for reliability mixture models under random censoringLaurentBordes81fb6e1ae2b3e2c3db66accf4929e230dma.utc.fr81241DidierChauveaua89af7fd6f7e2b2dea3139611c4ea364univ-orleans.fr711334DidierChauveaua89af7fd6f7e2b2dea3139611c4ea364univ-orleans.fr2012-04-06 10:17:092013-06-10 14:05:412012-04-062013-06-10 14:45:482013-06-10 14:45:482012-04-062013-06-10contributorDidierChauveaua89af7fd6f7e2b2dea3139611c4ea364univ-orleans.frCCSDhal-00685823https://hal.archives-ouvertes.fr/hal-00685823bordes:hal-0068582320122012CNRS - Centre national de la recherche scientifiqueUniversité d'OrléansLaboratoire de Mathématiques et de leurs Applications de PauCNRS-INSMI - INstitut des Sciences Mathématiques et de leurs InteractionsModelisation Systemes LangagesNot setEM and Stochastic EM algorithms for reliability mixture models under random censoringLaurentBordes81fb6e1ae2b3e2c3db66accf4929e230dma.utc.fr81241DidierChauveaua89af7fd6f7e2b2dea3139611c4ea364univ-orleans.fr711334EnglishEM algorithmfinite mixturesemiparametric mixturesreliabilitysurvival dataMathematics [math]/Statistics [math.ST]Statistics [stat]/Statistics Theory [stat.TH]Preprints, Working Papers, ...Mixture models in reliability bring a useful compromise between parametric and nonparametric models, when several failure modes are suspected. The classical methods for estimation in mixture models rarely handle the additional difficulty coming from the fact that lifetime data are often censored, in a deterministic or random way. We present in this paper several iterative methods based on EM and Stochastic EM methodology, that allow us to estimate parametric or semiparametric mixture models for randomly right censored lifetime data, provided they are identifiable. We consider different levels of completion for the (incomplete) observed data, and provide genuine or EM-like algorithms for several situations. In particular, we show that in censored semiparametric situations, a stochastic step is the only practical solution allowing computation of nonparametric estimates of the unknown survival function. The effectiveness of the new proposed algorithms are demonstrated in simulation studies and an actual dataset example.Laboratoire de Mathématiques et de leurs Applications [Pau]LMAP
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