An efficient interpolation technique for jump proposals in reversible-jump Markov chain Monte Carlo calculations
Selection among alternative theoretical models given an observed dataset is an important challenge in many areas of physics and astronomy. Reversible-jump Markov chain Monte Carlo (RJMCMC) is an extremely powerful technique for performing Bayesian model selection, but it suffers from a fundamental d...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Royal Society
2016
|
| Online Access: | http://hdl.handle.net/1721.1/100817 |