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Abstract
In this paper, we introduce maximum likelihood and Bayesian parameter estimation for the exponentiated discrete Weibull (EDW) distribution in presence of randomly right censored data. We also consider the inclusion of a cure fraction in the model. The performance of the maximum likelihood estimation approach is assessed by conducting an extensive simulation study with different sample sizes and different values for the parameters of the EDW distribution. The usefuness of the proposed model is illustrated with two examples considering real data sets.
Keywords
maximum likelihood estimation
survival analysis
cure fraction
Bayesian inference
Discrete distributions
Censored data
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Copyright © 2021 Pakistan Journal of Statistics and Operation Research
Creative Commons Attribution 4.0 International (CC BY 4.0)
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How to Cite
Achcar, J. A., Martinez, E. Z., Lopes de Freitas, B. C., & Peres, M. V. de O. (2021). Classical and Bayesian inference approaches for the exponentiated discrete Weibull model with censored data and a cure fraction. Pakistan Journal of Statistics and Operation Research, 17(2), 467-481. https://doi.org/10.18187/pjsor.v17i2.3693