A new rejection sampling method without using hat function

作者：Dai Hongsheng^*

来源：Bernoulli, 2017, 23(4A): 2434-2465.

DOI：10.3150/16-BEJ814

• conditioned Brownian motion
• coupling from the past
• diffusion bridges
• exact Monte Carlo simulation
• Langevin diffusion
• mixture models
• rejection sampling

This paper proposes a new exact simulation method, which simulates a realisation from a proposal density and then uses exact simulation of a Langevin diffusion to check whether the proposal should be accepted or rejected. Comparing to the existing coupling from the past method, the new method does not require constructing fast coalescence Markov chains. Comparing to the existing rejection sampling method, the new method does not require the proposal density function to bound the target density function. The new method is much more efficient than existing methods for certain problems. An application on exact simulation of the posterior of finite mixture models is presented.

• 出版日期2017-11