Estimation of the extreme survival probabilities from censored data
Închide
Conţinutul numărului revistei
Articolul precedent
Articolul urmator
707 5
Ultima descărcare din IBN:
2017-02-26 08:26
Căutarea după subiecte
similare conform CZU
519.2+519.248 (1)
Probabilitate. Statistică matematică (68)
SM ISO690:2012
GRAMA, Ion; TRICOT, Jean-Marie; PETIOT, Jean-Francois. Estimation of the extreme survival probabilities from censored data. In: Buletinul Academiei de Ştiinţe a Moldovei. Matematica. 2014, nr. 1(74), pp. 33-62. ISSN 1024-7696.
EXPORT metadate:
Google Scholar
Crossref
CERIF

DataCite
Dublin Core
Buletinul Academiei de Ştiinţe a Moldovei. Matematica
Numărul 1(74) / 2014 / ISSN 1024-7696

Estimation of the extreme survival probabilities from censored data
CZU: 519.2+519.248

Pag. 33-62

Grama Ion, Tricot Jean-Marie, Petiot Jean-Francois
 
Universite de Bretagne Sud
 
Disponibil în IBN: 18 iunie 2014


Rezumat

The Kaplan-Meier nonparametric estimator has become a standard tool for estimating a survival time distribution in a right censoring schema. However, if the censoring rate is high, this estimator does not provide a reliable estimation of the extreme survival probabilities. In this paper we propose to combine the nonparametric Kaplan-Meier estimator and a parametric-based model into one construction. The idea is to fit the tail of the survival function with a parametric model while for the remaining to use the Kaplan-Meier estimator. A procedure for the automatic choice of the location of the tail based on a goodness-of-fit test is proposed. This technique allows us to improve the estimation of the survival probabilities in the mid and long term. We perform numerical simulations which confirm the advantage of the proposed method.

Cuvinte-cheie
Adaptive estimation, censored data, model selection, survival analysis, survival probabilities,

prediction