- Bayesian inference for concave distribution functions is investigated. This is made by transforming a mixture of Dirichlet processes on the space of distribution functions to the space of concave distribution functions. We give a method for sampling from the posterior distribution using a Pólya urn scheme in combination with a Markov chain Monte Carlo algorithm. The methods are extended to estimation of concave distribution functions for incompletely observed data.
- Publication status:
- Publisher copy:
- Copyright date:
Nonparametric Bayes inference for concave distribution functions
If you are the owner of this record, you can report an update to it here: Report update to this record