A GENERAL ASYMPTOTIC THEORY FOR MAXIMUM LIKELIHOOD ESTIMATION IN SEMIPARAMETRIC REGRESSION MODELS WITH CENSORED DATA

We establish a general asymptotic theory for nonparametric maximum likelihood estimation in semiparametric regression models with right censored data. We identify a set of regularity conditions under which the nonparametric maximum likelihood estimators are consistent, asymptotically normal, and asy...

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Autors principals: Zeng, Donglin, Lin, D. Y.
Format: Artigo
Idioma:Inglês
Publicat: 2010
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Article
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC2888521/
https://ncbi.nlm.nih.gov/pubmed/20577580
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