Resumo

COELHO-BARROS, Emílio A. et al. Bayesian Inference for the Segmented Weibull Distribution. Rev.Colomb.Estad. [online]. 2019, vol.42, n.2, pp.225-243. ISSN 0120-1751.  https://doi.org/10.15446/rce.v42n2.76815.

In this paper, we introduce a Bayesian approach for segmented Weibull distributions which could be a good alternative to analyze medical survival data in the presence of censored observations and covariates. With the obtained Bayesian estimated change-points we could get an excellent fit of the proposed model to any data sets. With the proposed methodology, it is also possible to identify survival times intervals where a covariate could have significantly different effects when compared to other lifetime intervals, an important point under a clinical view. The obtained Bayesian estimates are obtained using standard Markov Chain Monte Carlo methods. Some examples with real data sets illustrate the proposed methodology and its potential clinical value.

Palavras-chave : Bayesian methods; Censored data; Change-points; Covariates; Segmented Weibull distribution.

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