Abstract
In this article, we use Bayesian reference analysis to consider the model of recurrent events with competing risks, where the sampling distribution of the observations due to some failure types is modeled through a proportional intensity homogeneous Poisson process and individuals are expected to experience repeated events along with the fixed covariates. The goal is to estimate the cause-specific intensity functions. Three reference priors are derived according to this model. Their associated posteriors are also discussed. The simulation work and real data application based on the reference priors and the classical likelihood approach show the efficiency of reference analysis.
| Original language | English |
|---|---|
| Pages (from-to) | 265-279 |
| Number of pages | 15 |
| Journal | Quality Technology and Quantitative Management |
| Volume | 11 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2014 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Bayesian analysis
- Competing risk
- Intensity function
- Poisson process
- Recurrent events
- Reference prior
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