Published

2019-07-01

Bayesian Inference For The Segmented Weibull Distribution

Inferencia Bayesiana Para Distribuciones Weibull Segmentadas

DOI:

https://doi.org/10.15446/rce.v42n2.76815

Keywords:

Segmented Weibull distribution, change-points, censored data, covariates, Bayesian methods. (en)
Distribución Weibull segmentada, puntos de cambio, datos censurados, covariables, métodos Bayesianos (es)

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Authors

  • Emilio A. Coelho-Barros Federal University of Technology
  • Jorge A. Achcar Universidade de São Paulo (USP)
  • Edson Z. Martinez Universidade de São Paulo (USP)
  • Nasser Davarzani Maastricht University
  • Heike I. Grabsch University of Leeds

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 efects 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.

En este artículo introducimos un nuevo modelo Bayesiano para distribuciones Weibull segmentadas, que puede ser una buena alternativa en el análisis de datos aplicados a la investigación en salud, con la presencia de censuras y covariables. Con este método basado en la estimación de puntosde cambio, hemos obtenido un excelente ajuste a los datos utilizados como ejemplos. De acuerdo con el modelo propuesto, fue posible identificar rangos de valores en las series temporales en que una variable independiente podría tener diferentes efectos. Este es un resultado importante desde el punto de vista clínico. Los estimados bayesianos fueron obtenidos usando métodos de Monte Carlo en Cadenas de Markov. Ejemplos basados en conjuntos de datos reales fueran usados para ilustrar el uso de los modelos propuestos y sus potenciales aplicaciones en investigaciones clínicas.

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How to Cite

APA

Coelho-Barros, E. A., Achcar, J. A., Martinez, E. Z., Davarzani, N. and Grabsch, H. I. (2019). Bayesian Inference For The Segmented Weibull Distribution. Revista Colombiana de Estadística, 42(2), 225–243. https://doi.org/10.15446/rce.v42n2.76815

ACM

[1]
Coelho-Barros, E.A., Achcar, J.A., Martinez, E.Z., Davarzani, N. and Grabsch, H.I. 2019. Bayesian Inference For The Segmented Weibull Distribution. Revista Colombiana de Estadística. 42, 2 (Jul. 2019), 225–243. DOI:https://doi.org/10.15446/rce.v42n2.76815.

ACS

(1)
Coelho-Barros, E. A.; Achcar, J. A.; Martinez, E. Z.; Davarzani, N.; Grabsch, H. I. Bayesian Inference For The Segmented Weibull Distribution. Rev. colomb. estad. 2019, 42, 225-243.

ABNT

COELHO-BARROS, E. A.; ACHCAR, J. A.; MARTINEZ, E. Z.; DAVARZANI, N.; GRABSCH, H. I. Bayesian Inference For The Segmented Weibull Distribution. Revista Colombiana de Estadística, [S. l.], v. 42, n. 2, p. 225–243, 2019. DOI: 10.15446/rce.v42n2.76815. Disponível em: https://revistas.unal.edu.co/index.php/estad/article/view/76815. Acesso em: 28 mar. 2025.

Chicago

Coelho-Barros, Emilio A., Jorge A. Achcar, Edson Z. Martinez, Nasser Davarzani, and Heike I. Grabsch. 2019. “Bayesian Inference For The Segmented Weibull Distribution”. Revista Colombiana De Estadística 42 (2):225-43. https://doi.org/10.15446/rce.v42n2.76815.

Harvard

Coelho-Barros, E. A., Achcar, J. A., Martinez, E. Z., Davarzani, N. and Grabsch, H. I. (2019) “Bayesian Inference For The Segmented Weibull Distribution”, Revista Colombiana de Estadística, 42(2), pp. 225–243. doi: 10.15446/rce.v42n2.76815.

IEEE

[1]
E. A. Coelho-Barros, J. A. Achcar, E. Z. Martinez, N. Davarzani, and H. I. Grabsch, “Bayesian Inference For The Segmented Weibull Distribution”, Rev. colomb. estad., vol. 42, no. 2, pp. 225–243, Jul. 2019.

MLA

Coelho-Barros, E. A., J. A. Achcar, E. Z. Martinez, N. Davarzani, and H. I. Grabsch. “Bayesian Inference For The Segmented Weibull Distribution”. Revista Colombiana de Estadística, vol. 42, no. 2, July 2019, pp. 225-43, doi:10.15446/rce.v42n2.76815.

Turabian

Coelho-Barros, Emilio A., Jorge A. Achcar, Edson Z. Martinez, Nasser Davarzani, and Heike I. Grabsch. “Bayesian Inference For The Segmented Weibull Distribution”. Revista Colombiana de Estadística 42, no. 2 (July 1, 2019): 225–243. Accessed March 28, 2025. https://revistas.unal.edu.co/index.php/estad/article/view/76815.

Vancouver

1.
Coelho-Barros EA, Achcar JA, Martinez EZ, Davarzani N, Grabsch HI. Bayesian Inference For The Segmented Weibull Distribution. Rev. colomb. estad. [Internet]. 2019 Jul. 1 [cited 2025 Mar. 28];42(2):225-43. Available from: https://revistas.unal.edu.co/index.php/estad/article/view/76815

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1. Jorge Alberto Achcar, Ricardo Puziol de Oliveira. (2022). Climate Change: Use of Non-Homogeneous Poisson Processes for Climate Data in Presence of a Change-Point. Environmental Modeling & Assessment, 27(2), p.385. https://doi.org/10.1007/s10666-021-09797-z.

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