Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/45377

TitlePresmoothed Landmark estimators of the transition probabilities
Author(s)Machado, Luís Meira
KeywordsKaplan-Meier
Multi-state model
Nonparametric estimation
Transition probabilities
Issue date2016
Abstract(s)Multi-state models can be successfully used to model complicated event history data, for example, describing stages in the disease progression of a patient. In these models one important goal is the estimation of the transition probabilities since they allow for long term prediction of the process. There have been several recent contributions for the estimation of the transition probabilities. Recently, de Uña- Álvarez and Meira-Machado (2015) proposed new estimators for these quantities, and their superiority with respect to the competing estimators has been proved in situations in which the Markov condition is violated. In this paper, we propose a modification of the estimator proposed by de Uña-Álvarez and Meira-Machado based on presmoothing. Simulations show that the presmoothed estimators may be much more efficient than the completely nonparametric estimator.
TypeConference paper
URIhttp://hdl.handle.net/1822/45377
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CMAT - Artigos em atas de conferências e capítulos de livros com arbitragem / Papers in proceedings of conferences and book chapters with peer review

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