Bayesian nonparametric survival analysis using mixture of Burr XII distributions
| Autor: | S. Bohlouri Hajjar, Soleiman Khazaei |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Statistics and Probability
021103 operations research Burr distribution Posterior probability 0211 other engineering and technologies Markov chain Monte Carlo 02 engineering and technology Mixture model 01 natural sciences Bayesian nonparametrics Dirichlet process 010104 statistics & probability symbols.namesake Modeling and Simulation Kernel (statistics) Statistics symbols 0101 mathematics Survival analysis Mathematics |
| Zdroj: | Communications in Statistics - Simulation and Computation. 47:2724-2738 |
| ISSN: | 1532-4141 0361-0918 |
| DOI: | 10.1080/03610918.2017.1359286 |
| Popis: | Recently, the Bayesian nonparametric approaches in survival studies attract much more attentions. Because of multimodality in survival data, the mixture models are very common. We introduce a Bayesian nonparametric mixture model with Burr distribution (Burr type XII) as the kernel. Since the Burr distribution shares good properties of common distributions on survival analysis, it has more flexibility than other distributions. By applying this model to simulated and real failure time datasets, we show the preference of this model and compare it with Dirichlet process mixture models with different kernels. The Markov chain Monte Carlo (MCMC) simulation methods to calculate the posterior distribution are used. |
| Databáze: | OpenAIRE |
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